{"image_file_name": "swig/exercising_255.jpg", "positive_caption": ["A man exercises his torso."], "negative_caption": ["A torso exercises for a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_0", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/preaching_116.jpg", "positive_caption": ["A preacher preaches to the onlooker."], "negative_caption": ["An onlooker preaches to the preacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/displaying_251.jpg", "positive_caption": ["A man displays a certificate."], "negative_caption": ["A certificate displays a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_2", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_139.jpg", "positive_caption": ["The people unveil the prize."], "negative_caption": ["A prize unveils people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_4", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_74.jpg", "positive_caption": ["A man unveils a statue."], "negative_caption": ["A statue unveils of a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_5", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sucking_143.jpg", "positive_caption": ["A woman sucks on a candy cane."], "negative_caption": ["A candy cane sucks a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_6", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/clapping_56.jpg", "positive_caption": ["A toddler claps out a hand."], "negative_caption": ["A hand claps at the toddler."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_7", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/parachuting_100.jpg", "positive_caption": ["The people parachute into the parachute."], "negative_caption": ["A parachute parachutes over the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_8", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_114.jpg", "positive_caption": ["A girl reads a book."], "negative_caption": ["A book reads about a girl."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_9", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_68.jpg", "positive_caption": ["A teacher teaches a student."], "negative_caption": ["A student teaches a teacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_10", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_5.jpg", "positive_caption": ["A dog pees on a fireplug."], "negative_caption": ["A fireplug pees the dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_11", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arching_231.jpg", "positive_caption": ["A man arches his back."], "negative_caption": ["A back arches toward the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_12", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rehabilitating_199.jpg", "positive_caption": ["A woman rehabilitates a person."], "negative_caption": ["A person rehabilitates a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_13", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_199.jpg", "positive_caption": ["The people package the food."], "negative_caption": ["A food packages the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_14", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_197.jpg", "positive_caption": ["The people package the food."], "negative_caption": ["A food packages the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_15", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/counting_103.jpg", "positive_caption": ["A person counts money."], "negative_caption": ["A money counts as a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_16", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wringing_140.jpg", "positive_caption": ["A person wrings out a towel."], "negative_caption": ["A towel wrings from my person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_17", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/talking_27.jpg", "positive_caption": ["A man talks with a cellular telephone."], "negative_caption": ["A telephone talks to a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_18", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_35.jpg", "positive_caption": ["The people disembark from ship."], "negative_caption": ["A ship disembarks people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_19", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/drooling_170.jpg", "positive_caption": ["A baby drools over clothing."], "negative_caption": ["A clothing drools over the baby."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_20", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/twirling_224.jpg", "positive_caption": ["A woman twirls on a baton."], "negative_caption": ["A baton twirls at the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_21", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/twirling_128.jpg", "positive_caption": ["A woman twirls on a baton."], "negative_caption": ["A baton twirls at the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_22", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_124.jpg", "positive_caption": ["An athlete punts on a soccer ball."], "negative_caption": ["A soccer ball punts at an athlete."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_23", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/riding_24.jpg", "positive_caption": ["A man rids the raft."], "negative_caption": ["A raft rids man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_24", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boating_46.jpg", "positive_caption": ["A person boats a motorboat."], "negative_caption": ["A motorboat boats a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_25", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boating_44.jpg", "positive_caption": ["A person boats a motorboat."], "negative_caption": ["A motorboat boats a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_26", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boating_55.jpg", "positive_caption": ["A person boats a motorboat."], "negative_caption": ["A motorboat boats a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_27", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_135.jpg", "positive_caption": ["The people disembark an airplane."], "negative_caption": ["An airplane disembarks people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_29", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_102.jpg", "positive_caption": ["The people disembark an airplane."], "negative_caption": ["An airplane disembarks people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_30", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/applauding_36.jpg", "positive_caption": ["A guest applauds a speaker."], "negative_caption": ["A speaker applauds a guest."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_31", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/inflating_144.jpg", "positive_caption": ["A man inflates his mouth."], "negative_caption": ["A mouth inflates like a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_32", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_259.jpg", "positive_caption": ["The people row in a boat."], "negative_caption": ["A boat rows behind the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_33", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/carving_74.jpg", "positive_caption": ["A person carves wood."], "negative_caption": ["A wood carves a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_34", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_10.jpg", "positive_caption": ["A woman reads through a book."], "negative_caption": ["A book reads about a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_36", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_150.jpg", "positive_caption": ["A woman reads through a book."], "negative_caption": ["A book reads about a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_37", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disciplining_110.jpg", "positive_caption": ["A woman disciplines a male child."], "negative_caption": ["A male child disciplines a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_38", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/swinging_131.jpg", "positive_caption": ["A woman swings from the sofa."], "negative_caption": ["A sofa swings toward a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_39", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_6.jpg", "positive_caption": ["A woman complains to a cockroach."], "negative_caption": ["A cockroach complains to a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_40", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/puckering_109.jpg", "positive_caption": ["A woman puckers her lip."], "negative_caption": ["A lip puckers at the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_41", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/puckering_155.jpg", "positive_caption": ["A woman puckers her lip."], "negative_caption": ["A lip puckers at the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_42", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/puckering_112.jpg", "positive_caption": ["A woman puckers her lip."], "negative_caption": ["A lip puckers at the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_43", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/puckering_199.jpg", "positive_caption": ["A woman puckers her lip."], "negative_caption": ["A lip puckers at the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_44", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hurling_20.jpg", "positive_caption": ["A man hurls the ball."], "negative_caption": ["A ball hurls at a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_46", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_235.jpg", "positive_caption": ["A woman bites her shoe."], "negative_caption": ["A shoe bites a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_47", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/heaving_42.jpg", "positive_caption": ["A man heaves a rock."], "negative_caption": ["A rock heaves a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_48", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_119.jpg", "positive_caption": ["An old man reads through a book."], "negative_caption": ["A book reads about an old man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_50", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/falling_136.jpg", "positive_caption": ["A sprinter falls off a racetrack."], "negative_caption": ["A racetrack falls to a sprinter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_51", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_34.jpg", "positive_caption": ["The people disembark from a ferry."], "negative_caption": ["A ferry disembarks people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_52", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_5.jpg", "positive_caption": ["The people disembark from a ferry."], "negative_caption": ["A ferry disembarks people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_53", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_240.jpg", "positive_caption": ["A person admires a woman."], "negative_caption": ["A woman admires such a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_54", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/smelling_2.jpg", "positive_caption": ["A male child smells the flow."], "negative_caption": ["A flow smells like a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_55", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/whistling_112.jpg", "positive_caption": ["An old man whistles with a finger."], "negative_caption": ["A finger whistles at a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_56", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/grilling_61.jpg", "positive_caption": ["A person grills a chicken."], "negative_caption": ["A chicken grills a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_57", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_145.jpg", "positive_caption": ["A man burns a card game."], "negative_caption": ["A card game burns a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_59", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flexing_38.jpg", "positive_caption": ["A man flexes his biceps."], "negative_caption": ["The biceps flex of a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_60", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_98.jpg", "positive_caption": ["A woman unveils the brass."], "negative_caption": ["The brass unveil was a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_61", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sniffing_185.jpg", "positive_caption": ["A dog sniffs the ground."], "negative_caption": ["A ground sniffs like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_62", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_77.jpg", "positive_caption": ["A woman slips into the ground."], "negative_caption": ["A ground slips from the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_63", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_110.jpg", "positive_caption": ["The people disembark a raft."], "negative_caption": ["A raft disembarks people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_65", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_154.jpg", "positive_caption": ["The people unveil a painting."], "negative_caption": ["A painting unveils the two people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_66", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_35.jpg", "positive_caption": ["The people unveil a painting."], "negative_caption": ["A painting unveils the two people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_67", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wringing_127.jpg", "positive_caption": ["A girl wrings fabric."], "negative_caption": ["A fabric wrings from the girl."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_68", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_19.jpg", "positive_caption": ["A parent encourages such a girl."], "negative_caption": ["A girl encourages her parent."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_69", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_172.jpg", "positive_caption": ["A parent scolds a child."], "negative_caption": ["A child scolds its parent."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_70", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_117.jpg", "positive_caption": ["A woman encourages a female child."], "negative_caption": ["A female child encourages such a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_71", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/heaving_86.jpg", "positive_caption": ["A man heaves a dumbbell."], "negative_caption": ["A dumbbell heaves like a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_72", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flexing_148.jpg", "positive_caption": ["A man flexes his torso."], "negative_caption": ["A torso flexes like a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_73", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_131.jpg", "positive_caption": ["A man encourages a child."], "negative_caption": ["A child encourages such a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_74", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_114.jpg", "positive_caption": ["A man encourages a child."], "negative_caption": ["A child encourages such a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_75", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gambling_253.jpg", "positive_caption": ["A man gambles on a chip."], "negative_caption": ["A chip gambles on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_76", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/paying_168.jpg", "positive_caption": ["A man pays a cashier."], "negative_caption": ["A cashier pays the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_77", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flipping_208.jpg", "positive_caption": ["The people flip a boat."], "negative_caption": ["A boat flips over the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_78", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunching_21.jpg", "positive_caption": ["A man hunches over his chess set."], "negative_caption": ["A chess set hunches like a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_79", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_41.jpg", "positive_caption": ["A woman teaches a child."], "negative_caption": ["A child teaches a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_80", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/turning_102.jpg", "positive_caption": ["A soccer player turns his head."], "negative_caption": ["A head turns toward a soccer player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_81", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_82.jpg", "positive_caption": ["A man presses the plunger."], "negative_caption": ["A plunger presses into the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_82", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shelling_55.jpg", "positive_caption": ["A chef shells up an oyster."], "negative_caption": ["An oyster shells chef."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_83", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_27.jpg", "positive_caption": ["A teacher trains the class."], "negative_caption": ["The class train the teacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_84", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_47.jpg", "positive_caption": ["The people commute by bicycle."], "negative_caption": ["A bicycle commutes the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_85", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/begging_156.jpg", "positive_caption": ["A beaver begs a woman."], "negative_caption": ["A woman begs for a beaver."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_86", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spanking_55.jpg", "positive_caption": ["A woman spanks her daughter."], "negative_caption": ["A daughter spanks a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_87", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wringing_12.jpg", "positive_caption": ["A person wrings fabric."], "negative_caption": ["A fabric wrings a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_88", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wringing_183.jpg", "positive_caption": ["A person wrings fabric."], "negative_caption": ["A fabric wrings a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_89", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_206.jpg", "positive_caption": ["A puppy nips a finger."], "negative_caption": ["A finger nips the puppy."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_90", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_13.jpg", "positive_caption": ["A puppy nips a finger."], "negative_caption": ["A finger nips the puppy."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_91", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boating_16.jpg", "positive_caption": ["A person boats a boat."], "negative_caption": ["A boat boats a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_92", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_174.jpg", "positive_caption": ["A woman encourages a male child."], "negative_caption": ["A male child encourages such a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_93", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plummeting_296.jpg", "positive_caption": ["A parachutist plummets from an airplane."], "negative_caption": ["An airplane plummets like a parachutist."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_94", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_328.jpg", "positive_caption": ["A dog tugs a rope."], "negative_caption": ["A rope tugs the dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_95", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_302.jpg", "positive_caption": ["A dog tugs a rope."], "negative_caption": ["A rope tugs the dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_96", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chiseling_6.jpg", "positive_caption": ["A man chisels a rock."], "negative_caption": ["A rock chisels a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_97", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_110.jpg", "positive_caption": ["A father scolds a male child."], "negative_caption": ["A male child scolds his father."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_98", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_6.jpg", "positive_caption": ["The people disembark from the airplane."], "negative_caption": ["An airplane disembarks people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_100", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_185.jpg", "positive_caption": ["A puppy tugs on a leash."], "negative_caption": ["A leash tugs the puppy."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_101", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_14.jpg", "positive_caption": ["A person works with art."], "negative_caption": ["An art works by a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_102", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_29.jpg", "positive_caption": ["A person tugs a power cord."], "negative_caption": ["A power cord tugs on a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_103", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wrinkling_31.jpg", "positive_caption": ["A girl wrinkles her nose."], "negative_caption": ["A nose wrinkles like a girl."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_104", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/clapping_55.jpg", "positive_caption": ["A comedian claps his hand."], "negative_caption": ["A hand claps like a comedian."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_105", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arching_3.jpg", "positive_caption": ["A cat arches over the spinal column."], "negative_caption": ["A spinal column arches like a cat."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_106", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_227.jpg", "positive_caption": ["A man calls for a land line."], "negative_caption": ["A land line calls for a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_107", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_1.jpg", "positive_caption": ["A man calls for a land line."], "negative_caption": ["A land line calls for a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_108", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunching_176.jpg", "positive_caption": ["A man hunches on a golf club."], "negative_caption": ["A golf club hunches the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_109", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kicking_168.jpg", "positive_caption": ["A man kicks a soccer ball."], "negative_caption": ["A soccer ball kicks a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_110", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ailing_51.jpg", "positive_caption": ["A man ails her arm."], "negative_caption": ["An arm ails the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_111", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/piloting_110.jpg", "positive_caption": ["A couple pilots a jet."], "negative_caption": ["A jet pilots a couple."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_112", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_18.jpg", "positive_caption": ["A puppy tugs at a knot."], "negative_caption": ["A knot tugs the puppy."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_114", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_181.jpg", "positive_caption": ["A man encourages a woman."], "negative_caption": ["A woman encourages a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_115", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/giggling_187.jpg", "positive_caption": ["A woman giggles with a man."], "negative_caption": ["A man giggles at a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_116", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/asking_51.jpg", "positive_caption": ["A young buck asks for a girl."], "negative_caption": ["A girl asks about a young buck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_117", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_35.jpg", "positive_caption": ["The people commute by train."], "negative_caption": ["A train commutes people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_118", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_166.jpg", "positive_caption": ["The people commute by train."], "negative_caption": ["A train commutes people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_119", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_132.jpg", "positive_caption": ["The people commute by train."], "negative_caption": ["A train commutes people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_120", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_9.jpg", "positive_caption": ["The people commute by train."], "negative_caption": ["A train commutes people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_121", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_206.jpg", "positive_caption": ["A middle-aged man reads a book."], "negative_caption": ["A book reads about a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_122", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_61.jpg", "positive_caption": ["The people disembark by boat."], "negative_caption": ["A boat disembarks people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_123", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_125.jpg", "positive_caption": ["The people board the bus."], "negative_caption": ["The bus board had six people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_124", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wrinkling_12.jpg", "positive_caption": ["A male child wrinkles his brow."], "negative_caption": ["A brow wrinkles like a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_125", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/grimacing_186.jpg", "positive_caption": ["A male child grimaces his hair."], "negative_caption": ["A hair grimaces like a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_126", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_177.jpg", "positive_caption": ["A couple forages for a plant."], "negative_caption": ["A plant forages for a couple."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_127", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_42.jpg", "positive_caption": ["A couple forages for a plant."], "negative_caption": ["A plant forages for a couple."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_128", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/paying_206.jpg", "positive_caption": ["A customer pays a cashier."], "negative_caption": ["A cashier pays the customer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_129", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pedaling_46.jpg", "positive_caption": ["A female pedals on a bicycle."], "negative_caption": ["A bicycle pedals by a female."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_130", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_194.jpg", "positive_caption": ["The people board a ship."], "negative_caption": ["A ship boards people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_131", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_17.jpg", "positive_caption": ["A man forages for a flower."], "negative_caption": ["A flower forages for man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_132", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_183.jpg", "positive_caption": ["A man sits on a roof."], "negative_caption": ["A roof sits over a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_133", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stinging_178.jpg", "positive_caption": ["A bee stings a person."], "negative_caption": ["A person stings a bee."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_134", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ducking_52.jpg", "positive_caption": ["A man ducks for a punch."], "negative_caption": ["A punch ducks a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_135", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_223.jpg", "positive_caption": ["A farmer works on picking."], "negative_caption": ["A picking works for a farmer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_136", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/waving_199.jpg", "positive_caption": ["The people wave a flag."], "negative_caption": ["A flag waves at people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_138", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_2.jpg", "positive_caption": ["A man tills up a cultivator."], "negative_caption": ["A cultivator tills man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_139", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/drooling_37.jpg", "positive_caption": ["A baby drools on a bib."], "negative_caption": ["A bib drools like a baby."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_140", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_372.jpg", "positive_caption": ["A woman admires a baby."], "negative_caption": ["A baby admires a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_141", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/carving_5.jpg", "positive_caption": ["A man carves from limestone."], "negative_caption": ["A limestone carves a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_142", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unplugging_155.jpg", "positive_caption": ["A person unplugs the central processing unit."], "negative_caption": ["A central processing unit unplugs the person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_143", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_134.jpg", "positive_caption": ["A woman calls for a land line."], "negative_caption": ["A land line calls for a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_144", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_148.jpg", "positive_caption": ["A woman calls for a land line."], "negative_caption": ["A land line calls for a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_145", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_17.jpg", "positive_caption": ["A woman calls for a land line."], "negative_caption": ["A land line calls for a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_146", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wrinkling_25.jpg", "positive_caption": ["A male child wrinkles his nose."], "negative_caption": ["A nose wrinkles like a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_147", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pedaling_42.jpg", "positive_caption": ["A rider pedals a bicycle."], "negative_caption": ["A bicycle pedals as a rider."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_148", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wringing_111.jpg", "positive_caption": ["A woman wrings out a swab."], "negative_caption": ["A swab wrings from the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_149", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wagging_64.jpg", "positive_caption": ["A dog wags a tail."], "negative_caption": ["A tail wags like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_150", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wagging_12.jpg", "positive_caption": ["A dog wags a tail."], "negative_caption": ["A tail wags like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_151", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wagging_198.jpg", "positive_caption": ["A dog wags a tail."], "negative_caption": ["A tail wags like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_152", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rehabilitating_94.jpg", "positive_caption": ["A woman rehabilitates her leg."], "negative_caption": ["A leg rehabilitates a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_153", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rehabilitating_204.jpg", "positive_caption": ["A woman rehabilitates her leg."], "negative_caption": ["A leg rehabilitates a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_154", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_15.jpg", "positive_caption": ["A female child reads through a book."], "negative_caption": ["A book reads a female child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_156", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sowing_154.jpg", "positive_caption": ["A person sows a finger."], "negative_caption": ["A finger sows a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_157", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tripping_200.jpg", "positive_caption": ["A woman trips across a floor."], "negative_caption": ["A floor trips over a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_158", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_88.jpg", "positive_caption": ["A woman encourages a young toddler."], "negative_caption": ["A toddler encourages a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_160", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/juggling_30.jpg", "positive_caption": ["A man juggles a bowling pin."], "negative_caption": ["A bowling pin juggles a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_161", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_202.jpg", "positive_caption": ["A woman teaches people."], "negative_caption": ["The people teach the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_162", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_98.jpg", "positive_caption": ["A woman teaches people."], "negative_caption": ["The people teach the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_163", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_302.jpg", "positive_caption": ["A woman teaches people."], "negative_caption": ["The people teach the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_164", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/descending_98.jpg", "positive_caption": ["The people descend on foot."], "negative_caption": ["A foot descends on the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_165", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sucking_49.jpg", "positive_caption": ["A horse sucks her breast."], "negative_caption": ["A breast sucks like a horse."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_166", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_233.jpg", "positive_caption": ["The people work in a garden."], "negative_caption": ["A garden works for the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_167", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_67.jpg", "positive_caption": ["A mother reassures her daughter."], "negative_caption": ["A daughter reassures her mother."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_168", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_238.jpg", "positive_caption": ["A coach teaches a student."], "negative_caption": ["A student teaches as a coach."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_169", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_285.jpg", "positive_caption": ["A farmer tills a cultivator."], "negative_caption": ["A cultivator tills a farmer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_170", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_171.jpg", "positive_caption": ["The people board a train."], "negative_caption": ["A train boards the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_171", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/applauding_173.jpg", "positive_caption": ["A person applauds the President of the United States."], "negative_caption": ["The President of the United States applaud such a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_172", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/clinging_330.jpg", "positive_caption": ["A koala clings to a tree."], "negative_caption": ["A tree clings to koala."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_173", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tackling_105.jpg", "positive_caption": ["An athlete tackles a man."], "negative_caption": ["A man tackles an athlete."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_174", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/braiding_133.jpg", "positive_caption": ["A person braids their hair."], "negative_caption": ["A hair braids a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_175", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/braiding_180.jpg", "positive_caption": ["A person braids their hair."], "negative_caption": ["A hair braids a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_176", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/braiding_132.jpg", "positive_caption": ["A person braids their hair."], "negative_caption": ["A hair braids a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_177", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_302.jpg", "positive_caption": ["A man bites into a branch."], "negative_caption": ["A branch bites a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_178", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/swinging_272.jpg", "positive_caption": ["A man swings on a rope."], "negative_caption": ["A rope swings toward the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_179", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_239.jpg", "positive_caption": ["The people camp in a tent."], "negative_caption": ["A tent camps the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_180", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_151.jpg", "positive_caption": ["The people camp in a tent."], "negative_caption": ["A tent camps the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_181", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_83.jpg", "positive_caption": ["The people camp in a tent."], "negative_caption": ["A tent camps the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_182", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_86.jpg", "positive_caption": ["The people camp in a tent."], "negative_caption": ["A tent camps the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_183", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wringing_15.jpg", "positive_caption": ["A woman wrings fabric."], "negative_caption": ["A fabric wrings from a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_185", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gardening_114.jpg", "positive_caption": ["A person gardens a spade."], "negative_caption": ["A spade gardens a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_186", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wading_68.jpg", "positive_caption": ["A American bison wads in a pond."], "negative_caption": ["A pond wads American bison."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_187", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_241.jpg", "positive_caption": ["An athlete emerges from the body of water."], "negative_caption": ["The body of water emerge an athlete."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_188", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_57.jpg", "positive_caption": ["An athlete rows in a kayak."], "negative_caption": ["A kayak rows as an athlete."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_189", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_203.jpg", "positive_caption": ["A woman scolds a male child."], "negative_caption": ["A male child scolds a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_190", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_87.jpg", "positive_caption": ["A boatman disembarks from the ship."], "negative_caption": ["A ship disembarks with a boatman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_191", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/fording_250.jpg", "positive_caption": ["A driver fords a sport utility."], "negative_caption": ["A sport utility fords a driver."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_192", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_118.jpg", "positive_caption": ["A mother reassures her child."], "negative_caption": ["A child reassures a mother."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_193", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_123.jpg", "positive_caption": ["A coach coaches a team."], "negative_caption": ["A team coaches a coach."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_194", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_168.jpg", "positive_caption": ["A man sits on a rock."], "negative_caption": ["A rock sits beside the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_195", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/puckering_119.jpg", "positive_caption": ["A man puckers his lip."], "negative_caption": ["A lip puckers like a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_196", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/puckering_182.jpg", "positive_caption": ["A man puckers his lip."], "negative_caption": ["A lip puckers like a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_197", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_172.jpg", "positive_caption": ["A woman teaches a female child."], "negative_caption": ["A female child teaches a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_198", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_253.jpg", "positive_caption": ["A woman teaches a female child."], "negative_caption": ["A child teaches a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_199", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_100.jpg", "positive_caption": ["A woman browses my shirt."], "negative_caption": ["A shirt browses at a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_201", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ramming_156.jpg", "positive_caption": ["A train rams the car."], "negative_caption": ["A car rams the train."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_202", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lifting_110.jpg", "positive_caption": ["A man lifts weight."], "negative_caption": ["A weight lifts a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_203", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lifting_297.jpg", "positive_caption": ["A man lifts weight."], "negative_caption": ["A weight lifts a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_204", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lifting_77.jpg", "positive_caption": ["A man lifts weight."], "negative_caption": ["A weight lifts a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_205", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_40.jpg", "positive_caption": ["A puppy nips a dog."], "negative_caption": ["A dog nips a puppy."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_206", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/dialing_63.jpg", "positive_caption": ["A person dials a telephone."], "negative_caption": ["A telephone dials a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_207", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stretching_291.jpg", "positive_caption": ["A person stretches their neck."], "negative_caption": ["A neck stretches like a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_208", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_150.jpg", "positive_caption": ["An athlete rows in a dinghy."], "negative_caption": ["A dinghy rows like an athlete."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_209", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_119.jpg", "positive_caption": ["A woman reassures her child."], "negative_caption": ["A child reassures a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_210", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chiseling_221.jpg", "positive_caption": ["A man chisels a statue."], "negative_caption": ["A statue chisels a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_211", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_148.jpg", "positive_caption": ["A pelican floats in water."], "negative_caption": ["A water floats on a pelican."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_212", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/counting_3.jpg", "positive_caption": ["A homo counts the ballot."], "negative_caption": ["A ballot counts as a homo."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_213", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_116.jpg", "positive_caption": ["A man lectures people."], "negative_caption": ["The people lecture the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_214", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_186.jpg", "positive_caption": ["A couple disembarks from the airplane."], "negative_caption": ["An airplane disembarks the couple."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_215", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_180.jpg", "positive_caption": ["A man trains people."], "negative_caption": ["The people train the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_216", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_7.jpg", "positive_caption": ["A coach teaches a boxer."], "negative_caption": ["A boxer teaches a coach."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_217", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_30.jpg", "positive_caption": ["A girl scolds a male child."], "negative_caption": ["A male child scolds the girl."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_218", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_194.jpg", "positive_caption": ["A football player punts a football."], "negative_caption": ["A football punts a football player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_219", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_123.jpg", "positive_caption": ["A football player punts a football."], "negative_caption": ["A football punts a football player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_220", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_196.jpg", "positive_caption": ["A football player punts a football."], "negative_caption": ["A football punts a football player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_221", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_173.jpg", "positive_caption": ["A football player punts a football."], "negative_caption": ["A football punts a football player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_222", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/educating_58.jpg", "positive_caption": ["A man educates a student."], "negative_caption": ["A student educates a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_223", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneading_209.jpg", "positive_caption": ["A person kneads the meat."], "negative_caption": ["A meat kneads a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_224", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/folding_204.jpg", "positive_caption": ["A person folds a sheet."], "negative_caption": ["A sheet folds over my person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_225", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/counting_133.jpg", "positive_caption": ["A person counts a bill."], "negative_caption": ["A bill counts a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_226", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/speaking_84.jpg", "positive_caption": ["A baby speaks on a telephone."], "negative_caption": ["A telephone speaks to a baby."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_227", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/swinging_80.jpg", "positive_caption": ["A male child swings on a swing."], "negative_caption": ["A swing swings toward a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_228", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/swinging_32.jpg", "positive_caption": ["A male child swings on a swing."], "negative_caption": ["A swing swings toward a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_229", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/offering_207.jpg", "positive_caption": ["A man offers me a hand."], "negative_caption": ["A hand offers a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_230", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_173.jpg", "positive_caption": ["A woman works on paper."], "negative_caption": ["A paper works for a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_231", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_257.jpg", "positive_caption": ["A woman trains people."], "negative_caption": ["The people train the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_232", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_52.jpg", "positive_caption": ["A soccer player reassures the goalkeeper."], "negative_caption": ["A goalkeeper reassures a soccer player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_233", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_153.jpg", "positive_caption": ["A woman aims a shotgun."], "negative_caption": ["A shotgun aims at the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_234", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_37.jpg", "positive_caption": ["A trainer trains an elephant."], "negative_caption": ["An elephant trains as a trainer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_235", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skating_27.jpg", "positive_caption": ["A person skates on an ice skate."], "negative_caption": ["An ice skate skates a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_236", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_95.jpg", "positive_caption": ["A coach trains with a player."], "negative_caption": ["A player trains a coach."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_237", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/clinging_185.jpg", "positive_caption": ["A butterfly clings to a flower."], "negative_caption": ["A flower clings to a butterfly."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_238", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bothering_126.jpg", "positive_caption": ["The police bother a young buck."], "negative_caption": ["A young buck bothers police."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_239", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_90.jpg", "positive_caption": ["A woman coaches people."], "negative_caption": ["The people coach the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_240", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_37.jpg", "positive_caption": ["The people row in a canoe."], "negative_caption": ["A canoe rows behind the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_241", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/climbing_191.jpg", "positive_caption": ["A figure climbs the stairs."], "negative_caption": ["The stairs climb the figure."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_242", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_102.jpg", "positive_caption": ["A man forages a berry."], "negative_caption": ["A berry forages for a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_243", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unplugging_6.jpg", "positive_caption": ["A person unplugs the wire."], "negative_caption": ["A wire unplugs a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_245", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_54.jpg", "positive_caption": ["A man tugs a bandage."], "negative_caption": ["A bandage tugs at a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_246", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/competing_108.jpg", "positive_caption": ["A basketball player competes in basketball."], "negative_caption": ["A basketball competes against a basketball player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_247", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sniffing_62.jpg", "positive_caption": ["A dog sniffs the grass."], "negative_caption": ["The grass sniff like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_248", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/providing_246.jpg", "positive_caption": ["A nurse provides for a patient."], "negative_caption": ["A patient provides for a nurse."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_249", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/providing_141.jpg", "positive_caption": ["A nurse provides for a patient."], "negative_caption": ["A patient provides for a nurse."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_250", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ducking_71.jpg", "positive_caption": ["A boxer ducks for a punch."], "negative_caption": ["A punch ducks the boxer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_251", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_80.jpg", "positive_caption": ["A person aims a gun."], "negative_caption": ["A gun aims at a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_252", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_288.jpg", "positive_caption": ["A whale emerges from the body of water."], "negative_caption": ["The body of water emerge like a whale."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_253", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_110.jpg", "positive_caption": ["A farmer tills a tiller."], "negative_caption": ["A tiller tills the farmer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_254", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/asking_129.jpg", "positive_caption": ["A nurse asks a patient."], "negative_caption": ["A patient asks for a nurse."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_255", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_268.jpg", "positive_caption": ["A person camps in a tent."], "negative_caption": ["A tent camps in person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_256", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camouflaging_240.jpg", "positive_caption": ["A hunter camouflages the vegetation."], "negative_caption": ["A vegetation camouflages the hunter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_257", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unplugging_59.jpg", "positive_caption": ["A person unplugs the cord."], "negative_caption": ["A cord unplugs a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_258", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unplugging_78.jpg", "positive_caption": ["A person unplugs the cord."], "negative_caption": ["A cord unplugs a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_259", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unplugging_192.jpg", "positive_caption": ["A person unplugs the cord."], "negative_caption": ["A cord unplugs a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_260", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unplugging_71.jpg", "positive_caption": ["A person unplugs the cord."], "negative_caption": ["A cord unplugs a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_261", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_135.jpg", "positive_caption": ["A woman leads the people."], "negative_caption": ["The people lead the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_262", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_106.jpg", "positive_caption": ["A man reassures a male child."], "negative_caption": ["A male child reassures a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_263", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/talking_282.jpg", "positive_caption": ["A woman talks to people."], "negative_caption": ["The people talk to the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_264", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/deflecting_190.jpg", "positive_caption": ["A soccer player deflects a soccer ball."], "negative_caption": ["A soccer ball deflects a soccer player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_265", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nuzzling_4.jpg", "positive_caption": ["A mother nuzzles her baby."], "negative_caption": ["A baby nuzzles its mother."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_266", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_210.jpg", "positive_caption": ["A colleague works on an undertaking."], "negative_caption": ["An undertaking works with a colleague."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_267", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_177.jpg", "positive_caption": ["A colleague works on an undertaking."], "negative_caption": ["An undertaking works with a colleague."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_268", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_28.jpg", "positive_caption": ["A male child reads from a book."], "negative_caption": ["A book reads a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_269", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_235.jpg", "positive_caption": ["A female child forages for pinecone."], "negative_caption": ["A pinecone forages for a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_270", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_35.jpg", "positive_caption": ["A punter punts a football."], "negative_caption": ["A football punts a punter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_271", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_12.jpg", "positive_caption": ["A punter punts a football."], "negative_caption": ["A football punts a punter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_272", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_182.jpg", "positive_caption": ["A punter punts a football."], "negative_caption": ["A football punts a punter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_273", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_72.jpg", "positive_caption": ["A man calls on a cellular telephone."], "negative_caption": ["A cellular telephone calls the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_274", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_20.jpg", "positive_caption": ["A man calls on a cellular telephone."], "negative_caption": ["A cellular telephone calls the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_275", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_120.jpg", "positive_caption": ["A dog nips at an owner."], "negative_caption": ["An owner nips the dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_276", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_61.jpg", "positive_caption": ["A man unveils the display."], "negative_caption": ["A display unveils the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_277", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/speaking_241.jpg", "positive_caption": ["A woman speaks to a female child."], "negative_caption": ["A child speaks to a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_278", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_129.jpg", "positive_caption": ["The people board a shuttle."], "negative_caption": ["A shuttle boards the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_279", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kicking_339.jpg", "positive_caption": ["A man kicks a sandbag."], "negative_caption": ["A sandbag kicks a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_280", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/blocking_273.jpg", "positive_caption": ["A gate blocks the truck."], "negative_caption": ["A truck blocks the gate."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_281", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_171.jpg", "positive_caption": ["A parent scolds the lass."], "negative_caption": ["The lass scold a parent."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_282", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/examining_66.jpg", "positive_caption": ["A doctor examines my mouth."], "negative_caption": ["A mouth examines the doctor."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_283", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rehabilitating_7.jpg", "positive_caption": ["A man rehabilitates his leg."], "negative_caption": ["A leg rehabilitates a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_284", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rehabilitating_247.jpg", "positive_caption": ["A man rehabilitates his leg."], "negative_caption": ["A leg rehabilitates a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_285", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_107.jpg", "positive_caption": ["A teacher teaches in a secondary school."], "negative_caption": ["A secondary school teaches a teacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_286", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shopping_20.jpg", "positive_caption": ["A woman shops for an apple."], "negative_caption": ["An apple shops delivery woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_287", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tripping_3.jpg", "positive_caption": ["A person trips across a rug."], "negative_caption": ["A rug trips over a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_288", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/clinging_65.jpg", "positive_caption": ["A fly clings to a leaf."], "negative_caption": ["A leaf clings to a fly."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_289", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/drooling_196.jpg", "positive_caption": ["A dog drools on the floor."], "negative_caption": ["A floor drools like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_290", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_74.jpg", "positive_caption": ["A woman floats on water."], "negative_caption": ["A water floats over the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_291", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/providing_228.jpg", "positive_caption": ["A doctor provides for a woman."], "negative_caption": ["A woman provides for a doctor."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_292", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/embracing_52.jpg", "positive_caption": ["A girl embraces a young buck."], "negative_caption": ["A young buck embraces a girl."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_293", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/eating_252.jpg", "positive_caption": ["A koala eats a leaf."], "negative_caption": ["A leaf eats a koala."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_294", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/educating_7.jpg", "positive_caption": ["A woman educates a male child."], "negative_caption": ["A male child educates a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_295", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/educating_179.jpg", "positive_caption": ["A woman educates a male child."], "negative_caption": ["A male child educates a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_296", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sucking_73.jpg", "positive_caption": ["An insect sucks on a flower."], "negative_caption": ["A flower sucks like an insect."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_297", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/restraining_73.jpg", "positive_caption": ["The people restrain the feline."], "negative_caption": ["A feline restrains people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_298", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_50.jpg", "positive_caption": ["A person packages you a chocolate."], "negative_caption": ["A chocolate packages a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_299", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/twirling_1.jpg", "positive_caption": ["A cowboy twirls in a Lasso."], "negative_caption": ["A lasso twirls like a cowboy."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_300", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kicking_154.jpg", "positive_caption": ["A soccer player kicks a soccer ball."], "negative_caption": ["A soccer ball kicks a soccer player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_301", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_185.jpg", "positive_caption": ["An athlete rows in a canoe."], "negative_caption": ["A canoe rows for an athlete."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_305", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/counting_14.jpg", "positive_caption": ["A young buck counts the cash."], "negative_caption": ["The cash count was a young buck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_306", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_188.jpg", "positive_caption": ["A man rows in a canal boat."], "negative_caption": ["A canal boat rows behind a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_307", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_86.jpg", "positive_caption": ["A man scolds a male child."], "negative_caption": ["A male child scolds a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_308", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ducking_54.jpg", "positive_caption": ["A child ducks under a rope."], "negative_caption": ["A rope ducks over a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_309", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_284.jpg", "positive_caption": ["A woman lectures people."], "negative_caption": ["The people lecture the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_310", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_76.jpg", "positive_caption": ["A woman lectures people."], "negative_caption": ["The people lecture the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_311", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_104.jpg", "positive_caption": ["A woman trains a child."], "negative_caption": ["A child trains with a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_312", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/selling_270.jpg", "positive_caption": ["A person sells such a merchandise."], "negative_caption": ["A merchandise sells a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_313", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_35.jpg", "positive_caption": ["An oarsman rows in a canoe."], "negative_caption": ["A canoe rows behind an oarsman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_314", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/asking_52.jpg", "positive_caption": ["A policeman asks about the people."], "negative_caption": ["The people ask for a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_315", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/preaching_14.jpg", "positive_caption": ["A curate preaches people."], "negative_caption": ["The people preach under a curate."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_316", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/preaching_190.jpg", "positive_caption": ["A curate preaches people."], "negative_caption": ["The people preach under a curate."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_317", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/preaching_126.jpg", "positive_caption": ["A curate preaches people."], "negative_caption": ["The people preach under a curate."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_318", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_84.jpg", "positive_caption": ["A man floats on water."], "negative_caption": ["A water floats over the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_321", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unplugging_157.jpg", "positive_caption": ["A person unplugs such a component."], "negative_caption": ["A component unplugs a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_322", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arranging_287.jpg", "positive_caption": ["A woman arranges for a flower."], "negative_caption": ["A flower arranges for a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_323", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunching_235.jpg", "positive_caption": ["A businessman hunches over a laptop."], "negative_caption": ["A laptop hunches like a businessman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_324", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/poking_16.jpg", "positive_caption": ["A woman pokes at the fire."], "negative_caption": ["A fire pokes at the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_325", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_79.jpg", "positive_caption": ["A person drives a car."], "negative_caption": ["A car drives a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_326", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneading_28.jpg", "positive_caption": ["A person kneads such a material."], "negative_caption": ["A material kneads a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_327", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_177.jpg", "positive_caption": ["A professor lectures people."], "negative_caption": ["The people lecture with a professor."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_328", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_70.jpg", "positive_caption": ["A professor lectures people."], "negative_caption": ["The people lecture with a professor."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_329", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_196.jpg", "positive_caption": ["A male child spears the fish."], "negative_caption": ["The fish spear a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_330", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_7.jpg", "positive_caption": ["A man coaches people."], "negative_caption": ["The people coach the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_332", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sewing_61.jpg", "positive_caption": ["A person sews the burlap."], "negative_caption": ["A burlap sews a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_333", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/speaking_273.jpg", "positive_caption": ["A mother speaks to her son."], "negative_caption": ["A son speaks to a mother."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_334", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_130.jpg", "positive_caption": ["A family camps in a tent."], "negative_caption": ["A tent camps a family."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_335", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_194.jpg", "positive_caption": ["A family camps in a tent."], "negative_caption": ["A tent camps a family."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_336", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/speaking_39.jpg", "positive_caption": ["A man speaks to an audience."], "negative_caption": ["An audience speaks to a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_337", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/speaking_248.jpg", "positive_caption": ["A man speaks to an audience."], "negative_caption": ["An audience speaks to a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_338", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_130.jpg", "positive_caption": ["A parent scolds such a child."], "negative_caption": ["A child scolds its parent."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_339", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_46.jpg", "positive_caption": ["A child bites my hand."], "negative_caption": ["A hand bites the child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_340", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slouching_69.jpg", "positive_caption": ["A man slouches in a chair."], "negative_caption": ["A chair slouches behind a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_342", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slouching_22.jpg", "positive_caption": ["A man slouches in a chair."], "negative_caption": ["A chair slouches behind a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_343", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slouching_193.jpg", "positive_caption": ["A man slouches in a chair."], "negative_caption": ["A chair slouches behind a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_344", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slouching_55.jpg", "positive_caption": ["A man slouches in a chair."], "negative_caption": ["A chair slouches behind a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_345", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slouching_159.jpg", "positive_caption": ["A man slouches in a chair."], "negative_caption": ["A chair slouches behind a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_346", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_181.jpg", "positive_caption": ["A soldier aims a sniper rifle."], "negative_caption": ["A sniper rifle aims at the soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_347", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_307.jpg", "positive_caption": ["A person presses in a picture."], "negative_caption": ["A picture presses into a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_348", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chiseling_195.jpg", "positive_caption": ["A man chisels a metallic element."], "negative_caption": ["A metallic element chisels man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_349", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lifting_176.jpg", "positive_caption": ["A man lifts a hammer."], "negative_caption": ["A hammer lifts a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_350", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kicking_269.jpg", "positive_caption": ["A male kicks a football."], "negative_caption": ["A football kicks a male."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_351", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_292.jpg", "positive_caption": ["A man presses the interface."], "negative_caption": ["An interface presses the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_352", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_92.jpg", "positive_caption": ["A football player stumbles to the ground."], "negative_caption": ["A ground stumbles on a football player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_353", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/competing_9.jpg", "positive_caption": ["A runner competes in a race."], "negative_caption": ["A race competes with a runner."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_354", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/competing_59.jpg", "positive_caption": ["A runner competes in a race."], "negative_caption": ["A race competes with a runner."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_355", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_242.jpg", "positive_caption": ["A woman floats on the body of water."], "negative_caption": ["A water floats over the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_356", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/twisting_101.jpg", "positive_caption": ["A man twists his beard."], "negative_caption": ["A beard twists like a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_358", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gardening_110.jpg", "positive_caption": ["A male child gardens a trowel."], "negative_caption": ["A trowel gardens a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_359", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rubbing_264.jpg", "positive_caption": ["A tiger rubs against the wood."], "negative_caption": ["A wood rubs against a tiger."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_360", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_87.jpg", "positive_caption": ["A person drives a boat."], "negative_caption": ["A boat drives a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_361", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_65.jpg", "positive_caption": ["A person packages food."], "negative_caption": ["A food packages a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_362", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/puckering_200.jpg", "positive_caption": ["A statue puckers its lip."], "negative_caption": ["A lip puckers like a statue."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_363", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_257.jpg", "positive_caption": ["A professor lectures as a student."], "negative_caption": ["A student lectures as a professor."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_366", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_144.jpg", "positive_caption": ["A professor lectures as a student."], "negative_caption": ["A student lectures as a professor."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_367", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_248.jpg", "positive_caption": ["A man aims a submachine gun."], "negative_caption": ["A submachine gun aims at a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_368", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_32.jpg", "positive_caption": ["A man reassures a woman."], "negative_caption": ["A woman reassures a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_371", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_16.jpg", "positive_caption": ["An athlete rows in a boat."], "negative_caption": ["A boat rows like an athlete."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_372", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_245.jpg", "positive_caption": ["An athlete rows in a boat."], "negative_caption": ["A boat rows like an athlete."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_373", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_76.jpg", "positive_caption": ["A man pees on the wall."], "negative_caption": ["A wall pees on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_374", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_304.jpg", "positive_caption": ["A killer whale emerges from water."], "negative_caption": ["A water emerges from a killer whale."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_375", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/milking_193.jpg", "positive_caption": ["A child milks a goat."], "negative_caption": ["A goat milks a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_376", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_104.jpg", "positive_caption": ["A man scolds a woman."], "negative_caption": ["A woman scolds a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_377", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/barbecuing_81.jpg", "positive_caption": ["A man barbecues the meat."], "negative_caption": ["A meat barbecues man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_379", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/barbecuing_38.jpg", "positive_caption": ["A man barbecues the meat."], "negative_caption": ["A meat barbecues man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_380", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/barbecuing_20.jpg", "positive_caption": ["A man barbecues the meat."], "negative_caption": ["A meat barbecues man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_381", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_45.jpg", "positive_caption": ["A man forages for a plant."], "negative_caption": ["A plant forages for man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_382", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_36.jpg", "positive_caption": ["A man spears the fish."], "negative_caption": ["The fish spear a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_383", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_6.jpg", "positive_caption": ["A man spears the fish."], "negative_caption": ["The fish spear a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_384", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_167.jpg", "positive_caption": ["A man spears the fish."], "negative_caption": ["The fish spear a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_385", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_195.jpg", "positive_caption": ["A man spears the fish."], "negative_caption": ["The fish spear a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_386", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_134.jpg", "positive_caption": ["A man spears the fish."], "negative_caption": ["The fish spear a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_387", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_168.jpg", "positive_caption": ["A man spears the fish."], "negative_caption": ["The fish spear a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_388", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/deflecting_131.jpg", "positive_caption": ["A male child deflects a soccer ball."], "negative_caption": ["A soccer ball deflects a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_389", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/educating_66.jpg", "positive_caption": ["A woman educates a child."], "negative_caption": ["A child educates a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_390", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/educating_205.jpg", "positive_caption": ["A woman educates a child."], "negative_caption": ["A child educates a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_391", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_245.jpg", "positive_caption": ["A woman instructs people."], "negative_caption": ["The people instruct the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_393", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_116.jpg", "positive_caption": ["A woman instructs people."], "negative_caption": ["The people instruct the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_394", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_98.jpg", "positive_caption": ["A woman instructs people."], "negative_caption": ["The people instruct the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_395", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/piloting_77.jpg", "positive_caption": ["A pilot pilots an airplane."], "negative_caption": ["An airplane pilots a pilot."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_396", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_233.jpg", "positive_caption": ["A female child reads from the book."], "negative_caption": ["A book reads a female child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_397", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bothering_112.jpg", "positive_caption": ["A male child bothers a middle-aged man."], "negative_caption": ["A man bothers with a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_398", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gnawing_65.jpg", "positive_caption": ["A dog gnaws a bone."], "negative_caption": ["A bone gnaws a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_399", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gnawing_380.jpg", "positive_caption": ["A dog gnaws a bone."], "negative_caption": ["A bone gnaws a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_400", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_177.jpg", "positive_caption": ["An athlete slips into a racetrack."], "negative_caption": ["A racetrack slips an athlete."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_401", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/puckering_32.jpg", "positive_caption": ["A male child puckers his lip."], "negative_caption": ["A lip puckers like a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_402", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_145.jpg", "positive_caption": ["A man instructs people."], "negative_caption": ["The people instruct such a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_404", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_52.jpg", "positive_caption": ["A man instructs people."], "negative_caption": ["The people instruct such a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_405", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_252.jpg", "positive_caption": ["A man instructs people."], "negative_caption": ["The people instruct such a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_406", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_178.jpg", "positive_caption": ["A man communicates with the people."], "negative_caption": ["The people communicate with man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_407", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_309.jpg", "positive_caption": ["A man communicates with the people."], "negative_caption": ["The people communicate with man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_409", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/typing_273.jpg", "positive_caption": ["A person types with a typewriter."], "negative_caption": ["A typewriter types like a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_410", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_139.jpg", "positive_caption": ["A scuba diver spears at the fish."], "negative_caption": ["The fish spear a scuba diver."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_411", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_12.jpg", "positive_caption": ["A horse stumbles on the soil."], "negative_caption": ["A soil stumbles over a horse."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_412", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/attacking_4.jpg", "positive_caption": ["A kitten attacks his foot."], "negative_caption": ["A foot attacks the kitten."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_413", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_83.jpg", "positive_caption": ["A person rows on a boat."], "negative_caption": ["A boat rows like a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_414", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_13.jpg", "positive_caption": ["A woman aims a gun."], "negative_caption": ["A gun aims at a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_415", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_224.jpg", "positive_caption": ["A bridge floats on water."], "negative_caption": ["A water floats over the bridge."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_416", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_72.jpg", "positive_caption": ["A man bites fish."], "negative_caption": ["The fish bite the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_417", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_207.jpg", "positive_caption": ["A woman reads from a novel."], "negative_caption": ["A novel reads about a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_418", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/releasing_40.jpg", "positive_caption": ["A person releases a bird."], "negative_caption": ["A bird releases a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_419", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/releasing_11.jpg", "positive_caption": ["A person releases a bird."], "negative_caption": ["A bird releases a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_420", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shouting_249.jpg", "positive_caption": ["A man shouts after a woman."], "negative_caption": ["A woman shouts at a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_421", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stitching_146.jpg", "positive_caption": ["A woman stitches the scissors."], "negative_caption": ["The scissors stitch the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_422", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/winking_13.jpg", "positive_caption": ["A man winks at a woman."], "negative_caption": ["A woman winks at a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_423", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calming_175.jpg", "positive_caption": ["A woman calms her dog."], "negative_caption": ["A dog calms a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_424", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_205.jpg", "positive_caption": ["A man aims for a paintball gun."], "negative_caption": ["A paintball gun aims at the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_425", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/detaining_24.jpg", "positive_caption": ["A policeman detains the woman."], "negative_caption": ["A woman detains a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_426", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disciplining_112.jpg", "positive_caption": ["A man disciplines a male child."], "negative_caption": ["A male child disciplines a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_427", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disciplining_133.jpg", "positive_caption": ["A man disciplines a male child."], "negative_caption": ["A male child disciplines a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_428", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_0.jpg", "positive_caption": ["A dog pees at a table."], "negative_caption": ["A table pees on a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_429", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/imitating_145.jpg", "positive_caption": ["A child imitates such a woman."], "negative_caption": ["A woman imitates such a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_430", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_303.jpg", "positive_caption": ["A child tugs a rope."], "negative_caption": ["A rope tugs the child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_432", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_154.jpg", "positive_caption": ["A person presses an application."], "negative_caption": ["An application presses on a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_433", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_223.jpg", "positive_caption": ["A person bites their fingernail."], "negative_caption": ["A fingernail bites a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_434", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_9.jpg", "positive_caption": ["A mosquito emerges from an exoskeleton."], "negative_caption": ["An exoskeleton emerges from the mosquito."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_435", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_44.jpg", "positive_caption": ["A woman commutes on a bicycle."], "negative_caption": ["A bicycle commutes with the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_436", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_99.jpg", "positive_caption": ["A woman commutes on a bicycle."], "negative_caption": ["A bicycle commutes with the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_437", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_194.jpg", "positive_caption": ["A woman commutes on a bicycle."], "negative_caption": ["A bicycle commutes with the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_438", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_56.jpg", "positive_caption": ["A female child camps in a tent."], "negative_caption": ["A tent camps a female child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_439", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_149.jpg", "positive_caption": ["A scuba diver spears a shark."], "negative_caption": ["A shark spears a scuba diver."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_440", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calming_91.jpg", "positive_caption": ["A mother calms her daughter."], "negative_caption": ["A daughter calms her mother."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_441", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/writing_262.jpg", "positive_caption": ["A teacher writes on a board."], "negative_caption": ["A board writes a teacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_442", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_113.jpg", "positive_caption": ["A soldier disembarks from the bus."], "negative_caption": ["The bus disembark the soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_443", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_163.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A telephone phones a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_444", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_66.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A telephone phones a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_445", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_31.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A telephone phones a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_446", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_180.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A telephone phones a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_447", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_103.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A telephone phones a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_448", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_122.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A telephone phones a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_449", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_220.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A telephone phones a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_450", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_73.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A telephone phones a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_451", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_299.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A telephone phones a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_452", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_167.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A telephone phones a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_453", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_168.jpg", "positive_caption": ["A young buck calls a cellular telephone."], "negative_caption": ["A cellular telephone calls the young buck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_454", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/clawing_228.jpg", "positive_caption": ["A cat claws at the post."], "negative_caption": ["A post claws a cat."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_455", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_214.jpg", "positive_caption": ["A man admires a woman."], "negative_caption": ["A woman admires such a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_456", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_148.jpg", "positive_caption": ["A teacher instructs a girl."], "negative_caption": ["A girl instructs a teacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_457", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stretching_270.jpg", "positive_caption": ["A lion stretches its back."], "negative_caption": ["A back stretches like a lion."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_458", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_203.jpg", "positive_caption": ["A farmer tills a tractor."], "negative_caption": ["A tractor tills a farmer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_459", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_173.jpg", "positive_caption": ["A farmer tills a tractor."], "negative_caption": ["A tractor tills a farmer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_460", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_172.jpg", "positive_caption": ["A farmer tills a tractor."], "negative_caption": ["A tractor tills a farmer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_461", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unplugging_83.jpg", "positive_caption": ["A person unplugs such a device."], "negative_caption": ["A device unplugs a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_462", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_230.jpg", "positive_caption": ["A man rows in a boat."], "negative_caption": ["A boat rows and a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_463", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_140.jpg", "positive_caption": ["A man rows in a boat."], "negative_caption": ["A boat rows and a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_464", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_64.jpg", "positive_caption": ["A man rows in a boat."], "negative_caption": ["A boat rows and a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_465", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_273.jpg", "positive_caption": ["A man rows in a boat."], "negative_caption": ["A boat rows and a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_466", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_171.jpg", "positive_caption": ["A man rows on a dinghy."], "negative_caption": ["A dinghy rows on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_467", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_48.jpg", "positive_caption": ["A male child phones the telephone."], "negative_caption": ["A telephone phones a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_468", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_103.jpg", "positive_caption": ["A dog sits on a floor."], "negative_caption": ["A floor sits like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_469", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_51.jpg", "positive_caption": ["An otter forages for the fish."], "negative_caption": ["The fish forage for the otter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_471", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_6.jpg", "positive_caption": ["A child tugs on a rope."], "negative_caption": ["A rope tugs the child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_472", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/drooling_215.jpg", "positive_caption": ["A dog drools on the ground."], "negative_caption": ["A ground drools at a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_473", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/drooling_127.jpg", "positive_caption": ["A dog drools on the ground."], "negative_caption": ["A ground drools at a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_474", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_187.jpg", "positive_caption": ["A businesswoman trains a customer."], "negative_caption": ["A customer trains a businesswoman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_475", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/smelling_1.jpg", "positive_caption": ["A dog smells the plant."], "negative_caption": ["A plant smells like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_476", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_171.jpg", "positive_caption": ["A swimmer emerges from the pond."], "negative_caption": ["A pond emerges with a swimmer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_479", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sniffing_399.jpg", "positive_caption": ["A feline sniffs the flower."], "negative_caption": ["A flower sniffs the feline."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_480", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_206.jpg", "positive_caption": ["A woman bites into her pipe."], "negative_caption": ["A pipe bites a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_481", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_56.jpg", "positive_caption": ["A man instructs a male child."], "negative_caption": ["A male child instructs a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_483", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_216.jpg", "positive_caption": ["A man instructs a male child."], "negative_caption": ["A male child instructs a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_484", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_58.jpg", "positive_caption": ["A man instructs a male child."], "negative_caption": ["A male child instructs a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_485", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bulldozing_184.jpg", "positive_caption": ["A person bulldozes the soil."], "negative_caption": ["A soil bulldozes a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_486", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bulldozing_114.jpg", "positive_caption": ["A person bulldozes the soil."], "negative_caption": ["A soil bulldozes a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_487", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_177.jpg", "positive_caption": ["A groundhog bites his ear."], "negative_caption": ["An ear bites like a groundhog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_488", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/selling_144.jpg", "positive_caption": ["A man sells his food."], "negative_caption": ["A food sells a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_489", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_72.jpg", "positive_caption": ["A dog urinates under a tree."], "negative_caption": ["A tree urinates on a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_490", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/mending_228.jpg", "positive_caption": ["A man mends an air conditioner."], "negative_caption": ["An air conditioner mends the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_491", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/releasing_58.jpg", "positive_caption": ["A woman releases a bird."], "negative_caption": ["A bird releases a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_492", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_9.jpg", "positive_caption": ["A woman calls a cellular telephone."], "negative_caption": ["A cellular telephone calls a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_493", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_78.jpg", "positive_caption": ["A woman calls a cellular telephone."], "negative_caption": ["A cellular telephone calls a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_494", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rotting_55.jpg", "positive_caption": ["A rabbit rots on the ground."], "negative_caption": ["A ground rots like a rabbit."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_495", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_120.jpg", "positive_caption": ["A woman skips a jump rope."], "negative_caption": ["A rope skips toward the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_497", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_122.jpg", "positive_caption": ["A passenger disembarks an airplane."], "negative_caption": ["An airplane disembarks without a passenger."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_498", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_147.jpg", "positive_caption": ["A man trains a woman."], "negative_caption": ["A woman trains a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_499", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_188.jpg", "positive_caption": ["A man trains a woman."], "negative_caption": ["A woman trains a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_500", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_155.jpg", "positive_caption": ["A man trains a woman."], "negative_caption": ["A woman trains a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_501", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_6.jpg", "positive_caption": ["A man slips to the floor."], "negative_caption": ["A floor slips under a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_502", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_18.jpg", "positive_caption": ["A man camps in a tent."], "negative_caption": ["A tent camps for a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_503", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_128.jpg", "positive_caption": ["A man camps in a tent."], "negative_caption": ["A tent camps for a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_504", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_107.jpg", "positive_caption": ["A man camps in a tent."], "negative_caption": ["A tent camps for a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_505", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/licking_285.jpg", "positive_caption": ["A dog licks my neck."], "negative_caption": ["A neck licks like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_506", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tying_222.jpg", "positive_caption": ["A child ties up a rope."], "negative_caption": ["A rope ties the child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_508", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_63.jpg", "positive_caption": ["A killer whale emerges from the body of water."], "negative_caption": ["The body of water emerge like a killer whale."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_509", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_231.jpg", "positive_caption": ["A wolf hunts the deer."], "negative_caption": ["The deer hunt the wolf."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_510", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_23.jpg", "positive_caption": ["A cheetah hunts a deer."], "negative_caption": ["The deer hunt a cheetah."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_511", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wrinkling_186.jpg", "positive_caption": ["An old woman wrinkles her brow."], "negative_caption": ["A brow wrinkles like an old woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_512", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_289.jpg", "positive_caption": ["A person presses a computer."], "negative_caption": ["A computer presses a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_513", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_82.jpg", "positive_caption": ["A woman instructs a passenger."], "negative_caption": ["A passenger instructs a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_514", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_65.jpg", "positive_caption": ["A female child complains to a woman."], "negative_caption": ["A woman complains about a female child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_515", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_250.jpg", "positive_caption": ["A statue pees on earth."], "negative_caption": ["An earth pees on the statue."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_516", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stretching_176.jpg", "positive_caption": ["A woman stretches her leg."], "negative_caption": ["A leg stretches toward the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_517", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_60.jpg", "positive_caption": ["A man leads the sheep."], "negative_caption": ["The sheep lead the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_518", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/panhandling_89.jpg", "positive_caption": ["A man panhandles people."], "negative_caption": ["The people panhandle the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_519", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_147.jpg", "positive_caption": ["A bird nips at the fish."], "negative_caption": ["The fish nip the bird."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_520", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_308.jpg", "positive_caption": ["A man pees over a tree."], "negative_caption": ["A tree pees on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_521", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/riding_69.jpg", "positive_caption": ["A man rids the statue."], "negative_caption": ["A statue rids a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_522", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_116.jpg", "positive_caption": ["A woman skips down a jump rope."], "negative_caption": ["A jump rope skips toward the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_523", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tripping_27.jpg", "positive_caption": ["A man trips across a floor."], "negative_caption": ["A floor trips a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_524", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bulldozing_91.jpg", "positive_caption": ["A man bulldozes the soil."], "negative_caption": ["A soil bulldozes man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_525", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plummeting_33.jpg", "positive_caption": ["A man plummets from a helicopter."], "negative_caption": ["A helicopter plummets on man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_526", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boating_101.jpg", "positive_caption": ["A male child boats in a canoe."], "negative_caption": ["A canoe boats a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_527", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_234.jpg", "positive_caption": ["A cat pees over a Kitty Litter."], "negative_caption": ["A Kitty Litter pees on a cat."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_528", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_198.jpg", "positive_caption": ["A man coaches a male child."], "negative_caption": ["A male child coaches a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_529", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_0.jpg", "positive_caption": ["A buck chases after the deer."], "negative_caption": ["The deer chase the deer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_530", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_157.jpg", "positive_caption": ["An old man coaches people."], "negative_caption": ["The people coach the old man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_531", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/clawing_120.jpg", "positive_caption": ["A woman claws at a man."], "negative_caption": ["A man claws at a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_532", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_101.jpg", "positive_caption": ["A soldier leads a troop."], "negative_caption": ["A troop leads a soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_534", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_215.jpg", "positive_caption": ["A man coaches a woman."], "negative_caption": ["A woman coaches a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_535", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_195.jpg", "positive_caption": ["A policeman arrests a man."], "negative_caption": ["A man arrests a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_536", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_186.jpg", "positive_caption": ["A policeman arrests a man."], "negative_caption": ["A man arrests a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_537", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_237.jpg", "positive_caption": ["A policeman arrests a man."], "negative_caption": ["A man arrests a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_538", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_108.jpg", "positive_caption": ["A policeman arrests a man."], "negative_caption": ["A man arrests a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_539", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_198.jpg", "positive_caption": ["A man bites his nail."], "negative_caption": ["A nail bites a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_540", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_361.jpg", "positive_caption": ["A male child admires an old man."], "negative_caption": ["A man admires a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_541", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_296.jpg", "positive_caption": ["A woman phones a telephone."], "negative_caption": ["A telephone phones a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_542", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_180.jpg", "positive_caption": ["A man pees over a wall."], "negative_caption": ["A wall pees on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_543", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_119.jpg", "positive_caption": ["A man pees over a wall."], "negative_caption": ["A wall pees on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_544", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_144.jpg", "positive_caption": ["A man pees over a wall."], "negative_caption": ["A wall pees on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_545", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_84.jpg", "positive_caption": ["A child urinates under a tree."], "negative_caption": ["A tree urinates on a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_546", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/displaying_34.jpg", "positive_caption": ["A speaker displays a report."], "negative_caption": ["A report displays on a speaker."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_547", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_186.jpg", "positive_caption": ["A person tills up a tractor."], "negative_caption": ["A tractor tills a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_548", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_60.jpg", "positive_caption": ["A football player slips onto the football field."], "negative_caption": ["A football field slips a football player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_549", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_47.jpg", "positive_caption": ["A dog nips at the auricle."], "negative_caption": ["An auricle nips a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_550", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plowing_157.jpg", "positive_caption": ["A man plows over a cow."], "negative_caption": ["A cow plows over a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_551", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_124.jpg", "positive_caption": ["A man commutes on a bicycle."], "negative_caption": ["A bicycle commutes a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_553", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_60.jpg", "positive_caption": ["A man commutes on a bicycle."], "negative_caption": ["A bicycle commutes a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_554", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_98.jpg", "positive_caption": ["A man commutes on a bicycle."], "negative_caption": ["A bicycle commutes a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_555", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_108.jpg", "positive_caption": ["A man commutes on a bicycle."], "negative_caption": ["A bicycle commutes a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_556", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_210.jpg", "positive_caption": ["A man commutes on a bicycle."], "negative_caption": ["A bicycle commutes a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_557", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_111.jpg", "positive_caption": ["A man commutes on a bicycle."], "negative_caption": ["A bicycle commutes a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_558", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_203.jpg", "positive_caption": ["A man instructs his people."], "negative_caption": ["The people instruct such a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_559", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_3.jpg", "positive_caption": ["A soldier disembarks a ship."], "negative_caption": ["A ship disembarks a soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_560", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baking_62.jpg", "positive_caption": ["A woman bakes me a cake."], "negative_caption": ["A cake bakes a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_562", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_228.jpg", "positive_caption": ["A businesswoman trains a colleague."], "negative_caption": ["A colleague trains as a businesswoman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_564", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_21.jpg", "positive_caption": ["A woman works at work."], "negative_caption": ["A work works for a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_565", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_141.jpg", "positive_caption": ["A young buck punts a football."], "negative_caption": ["A football punts for a young buck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_566", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_121.jpg", "positive_caption": ["A young buck punts a football."], "negative_caption": ["A football punts for a young buck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_567", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/adjusting_286.jpg", "positive_caption": ["A person adjusts the module."], "negative_caption": ["A module adjusts to a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_569", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_98.jpg", "positive_caption": ["A conductor leads a marching band."], "negative_caption": ["A marching band leads the band."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_570", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_160.jpg", "positive_caption": ["A man calls on telephone."], "negative_caption": ["A telephone calls the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_571", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/miming_141.jpg", "positive_caption": ["A mime mimes happiness."], "negative_caption": ["The happiness mime was a mime."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_572", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_100.jpg", "positive_caption": ["A woman disembarks an airplane."], "negative_caption": ["An airplane disembarks a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_574", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_59.jpg", "positive_caption": ["A woman disembarks an airplane."], "negative_caption": ["An airplane disembarks a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_575", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_30.jpg", "positive_caption": ["A policeman frisks the work force."], "negative_caption": ["A work force frisks a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_576", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_189.jpg", "positive_caption": ["A young buck packages up a broom."], "negative_caption": ["A broom packages the young buck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_577", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_93.jpg", "positive_caption": ["A woman phones the telephone."], "negative_caption": ["A telephone phones a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_578", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ducking_68.jpg", "positive_caption": ["A man ducks behind a door."], "negative_caption": ["A door ducks behind a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_579", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/talking_170.jpg", "positive_caption": ["An artist talks to a crowd."], "negative_caption": ["A crowd talks about the artist."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_580", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/begging_121.jpg", "positive_caption": ["A man begs for a woman."], "negative_caption": ["A woman begs for a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_581", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_345.jpg", "positive_caption": ["A woman tugs a rope."], "negative_caption": ["A rope tugs the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_582", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_288.jpg", "positive_caption": ["A woman communicates with a man."], "negative_caption": ["A man communicates with a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_583", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_82.jpg", "positive_caption": ["A man works the building."], "negative_caption": ["A building works for man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_584", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pouncing_97.jpg", "positive_caption": ["A fox pounces on the snow."], "negative_caption": ["A snow pounces on a fox."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_585", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_227.jpg", "positive_caption": ["A woman admires her child."], "negative_caption": ["A child admires such a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_586", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_143.jpg", "positive_caption": ["The people skip the rope."], "negative_caption": ["A rope skips people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_587", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shushing_24.jpg", "positive_caption": ["A man shushes people."], "negative_caption": ["The people shush the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_588", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_166.jpg", "positive_caption": ["A child camps in a tent."], "negative_caption": ["A tent camps a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_589", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/detaining_218.jpg", "positive_caption": ["A policeman detains the man."], "negative_caption": ["A man detains a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_590", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skating_185.jpg", "positive_caption": ["A hockey player skates on an ice skate."], "negative_caption": ["An ice skate skates a hockey player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_591", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flapping_183.jpg", "positive_caption": ["A bird flaps its wing."], "negative_caption": ["A wing flaps like a bird."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_592", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flapping_33.jpg", "positive_caption": ["A bird flaps its wing."], "negative_caption": ["A wing flaps like a bird."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_593", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flapping_48.jpg", "positive_caption": ["A bird flaps its wing."], "negative_caption": ["A wing flaps like a bird."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_594", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_220.jpg", "positive_caption": ["The police arrest a male."], "negative_caption": ["A male arrests police."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_595", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_281.jpg", "positive_caption": ["A man emerges from a swimming pool."], "negative_caption": ["A swimming pool emerges behind a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_596", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_192.jpg", "positive_caption": ["A man burns the cruiser."], "negative_caption": ["A cruiser burns over a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_597", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_37.jpg", "positive_caption": ["A man disembarks an airplane."], "negative_caption": ["An airplane disembarks a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_598", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shouting_150.jpg", "positive_caption": ["A male child shouts at a female child."], "negative_caption": ["A female child shouts at a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_599", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_207.jpg", "positive_caption": ["A man tills up a tractor."], "negative_caption": ["A tractor tills up a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_600", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_238.jpg", "positive_caption": ["A dog hunts a rabbit."], "negative_caption": ["A rabbit hunts a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_601", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_115.jpg", "positive_caption": ["A man skips a jump rope."], "negative_caption": ["A jump rope skips the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_602", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/confronting_162.jpg", "positive_caption": ["A demonstrator confronts the police."], "negative_caption": ["The police confront a demonstrator."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_603", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/taxiing_77.jpg", "positive_caption": ["An airplane taxis the water."], "negative_caption": ["A water taxis an airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_604", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wading_44.jpg", "positive_caption": ["A crane wads the body of water."], "negative_caption": ["The body of water wad like a crane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_605", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pushing_75.jpg", "positive_caption": ["A woman pushes against a boulder."], "negative_caption": ["A boulder pushes past the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_606", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_82.jpg", "positive_caption": ["A man calls the telephone."], "negative_caption": ["A telephone calls the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_607", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_15.jpg", "positive_caption": ["A radiologist reassures a patient."], "negative_caption": ["A patient reassures the radiologist."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_608", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_196.jpg", "positive_caption": ["The police arrest such a person."], "negative_caption": ["A person arrests police."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_609", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_92.jpg", "positive_caption": ["A soldier boards a ship."], "negative_caption": ["A ship boards a soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_610", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_52.jpg", "positive_caption": ["A soldier boards a ship."], "negative_caption": ["A ship boards a soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_611", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_141.jpg", "positive_caption": ["A woman packages paperwork."], "negative_caption": ["A paperwork packages the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_613", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_84.jpg", "positive_caption": ["A girl disembarks an airplane."], "negative_caption": ["An airplane disembarks the girl."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_614", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_34.jpg", "positive_caption": ["The police arrest a woman."], "negative_caption": ["A woman arrests police."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_615", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_148.jpg", "positive_caption": ["The police arrest a woman."], "negative_caption": ["A woman arrests police."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_616", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_110.jpg", "positive_caption": ["The police arrest a woman."], "negative_caption": ["A woman arrests police."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_617", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interviewing_240.jpg", "positive_caption": ["A woman interviews a man."], "negative_caption": ["A man interviews a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_618", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/assembling_378.jpg", "positive_caption": ["A man assembles a bicycle."], "negative_caption": ["A bicycle assembles around a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_619", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/fetching_140.jpg", "positive_caption": ["A male child fetches water."], "negative_caption": ["A water fetches up a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_620", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_54.jpg", "positive_caption": ["A mother scolds her son."], "negative_caption": ["A son scolds his mother."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_621", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_190.jpg", "positive_caption": ["A man aims a bow and arrow."], "negative_caption": ["A bow aims at the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_622", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/carrying_382.jpg", "positive_caption": ["A man carries a backpack."], "negative_caption": ["A backpack carries a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_623", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_119.jpg", "positive_caption": ["A soccer player stumbles onto the ground."], "negative_caption": ["A ground stumbles like a soccer player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_624", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_122.jpg", "positive_caption": ["A woman instructs a young person."], "negative_caption": ["A young person instructs a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_625", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/paying_77.jpg", "positive_caption": ["A man pays for a cashier."], "negative_caption": ["A cashier pays the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_626", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/mending_70.jpg", "positive_caption": ["A man mends the fabric."], "negative_caption": ["A fabric mends a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_627", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/detaining_124.jpg", "positive_caption": ["A watchman detains the man."], "negative_caption": ["A man detains the watchman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_628", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/licking_128.jpg", "positive_caption": ["A lion licks a cub."], "negative_caption": ["A cub licks a lion."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_629", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tripping_218.jpg", "positive_caption": ["A man trips on his foot."], "negative_caption": ["A foot trips a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_630", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_79.jpg", "positive_caption": ["A dog nips its owner."], "negative_caption": ["An owner nips the dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_631", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_202.jpg", "positive_caption": ["A dog nips its owner."], "negative_caption": ["An owner nips the dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_632", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plowing_290.jpg", "positive_caption": ["A man plows a horse."], "negative_caption": ["A horse plows over a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_633", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slouching_35.jpg", "positive_caption": ["A male child slouches on a sofa."], "negative_caption": ["A sofa slouches like a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_635", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_82.jpg", "positive_caption": ["A helicopter lands on the ground."], "negative_caption": ["A ground lands helicopter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_636", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_132.jpg", "positive_caption": ["A helicopter lands on the ground."], "negative_caption": ["A ground lands helicopter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_637", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_191.jpg", "positive_caption": ["A helicopter lands on the ground."], "negative_caption": ["A ground lands helicopter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_638", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_121.jpg", "positive_caption": ["A puppy tugs a jet."], "negative_caption": ["A jet tugs a puppy."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_639", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/talking_77.jpg", "positive_caption": ["A woman talks to a man."], "negative_caption": ["A man talks to a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_640", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interrogating_177.jpg", "positive_caption": ["A man interrogates a woman."], "negative_caption": ["A woman interrogates a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_646", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interrogating_35.jpg", "positive_caption": ["A man interrogates a woman."], "negative_caption": ["A woman interrogates a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_647", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pushing_326.jpg", "positive_caption": ["A man pushes a jeep."], "negative_caption": ["A jeep pushes past a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_648", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slouching_70.jpg", "positive_caption": ["A male child slouches in a chair."], "negative_caption": ["A chair slouches toward a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_649", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_101.jpg", "positive_caption": ["The police arrest a demonstrator."], "negative_caption": ["A demonstrator arrests police."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_650", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_13.jpg", "positive_caption": ["A woman phones a cellular telephone."], "negative_caption": ["A cellular telephone phones a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_651", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_147.jpg", "positive_caption": ["A woman phones a cellular telephone."], "negative_caption": ["A telephone phones a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_652", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_166.jpg", "positive_caption": ["A woman phones a cellular telephone."], "negative_caption": ["A telephone phones a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_653", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/imitating_63.jpg", "positive_caption": ["A veterinarian imitates such a dog."], "negative_caption": ["A dog imitates a veterinarian."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_654", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_51.jpg", "positive_caption": ["A woman reads from a textbook."], "negative_caption": ["A textbook reads about a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_656", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_59.jpg", "positive_caption": ["A man unveils the award."], "negative_caption": ["An award unveils the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_657", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_162.jpg", "positive_caption": ["A lion cub nips at the lioness."], "negative_caption": ["The lioness nip is a lion cub."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_660", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/assembling_147.jpg", "positive_caption": ["A soldier assembles a bomb."], "negative_caption": ["A bomb assembles the soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_661", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nagging_109.jpg", "positive_caption": ["A mother nags her child."], "negative_caption": ["A child nags at a mother."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_662", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_394.jpg", "positive_caption": ["A dog bites my hand."], "negative_caption": ["A hand bites the dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_663", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_77.jpg", "positive_caption": ["A man leads a group."], "negative_caption": ["A group leads to a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_664", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tripping_61.jpg", "positive_caption": ["A man trips on his leg."], "negative_caption": ["A leg trips a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_665", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pedaling_233.jpg", "positive_caption": ["A male child pedals a bicycle."], "negative_caption": ["A bicycle pedals with a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_666", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/buttoning_83.jpg", "positive_caption": ["A woman buttons up a bridal gown."], "negative_caption": ["A bridal gown buttons for a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_667", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hoeing_216.jpg", "positive_caption": ["A farmer hoes weed."], "negative_caption": ["A weed hoes a farmer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_668", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bandaging_136.jpg", "positive_caption": ["A teacher bandages a girl."], "negative_caption": ["A girl bandages her teacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_669", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/embracing_174.jpg", "positive_caption": ["A man embraces a woman."], "negative_caption": ["A woman embraces a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_671", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_158.jpg", "positive_caption": ["A woman complains to a man."], "negative_caption": ["A man complains to a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_674", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_169.jpg", "positive_caption": ["A patient complains to a doctor."], "negative_caption": ["A doctor complains to a patient."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_677", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_90.jpg", "positive_caption": ["A man skips down a jump rope."], "negative_caption": ["A jump rope skips the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_678", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/deflecting_13.jpg", "positive_caption": ["A man deflects a punch."], "negative_caption": ["A punch deflects the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_679", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_1.jpg", "positive_caption": ["A man complains to a waiter."], "negative_caption": ["A waiter complains to the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_680", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/grilling_114.jpg", "positive_caption": ["A person grills up the food."], "negative_caption": ["A food grills a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_681", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_10.jpg", "positive_caption": ["A ballplayer complains to an umpire."], "negative_caption": ["An umpire complains to the ballplayer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_682", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tackling_118.jpg", "positive_caption": ["A soccer player tackles the opposition."], "negative_caption": ["A soccer player tackles a soccer player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_683", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_77.jpg", "positive_caption": ["A man communicates with a woman."], "negative_caption": ["A woman communicates with a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_684", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wringing_84.jpg", "positive_caption": ["A chef wrings cream."], "negative_caption": ["A cream wrings a chef."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_687", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flapping_128.jpg", "positive_caption": ["A duck flaps its wing."], "negative_caption": ["A wing flaps like a duck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_688", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/clawing_153.jpg", "positive_caption": ["A cat claws at the table."], "negative_caption": ["A table claws like a cat."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_690", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/breaking_17.jpg", "positive_caption": ["A person breaks a window."], "negative_caption": ["A window breaks a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_691", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_246.jpg", "positive_caption": ["A man tugs a rope."], "negative_caption": ["A rope tugs the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_693", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_258.jpg", "positive_caption": ["A man tugs a rope."], "negative_caption": ["A rope tugs the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_694", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stretching_309.jpg", "positive_caption": ["A coyote stretches its mouth."], "negative_caption": ["A mouth stretches like a coyote."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_695", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_233.jpg", "positive_caption": ["An antelope chases a rabbit."], "negative_caption": ["A rabbit chases after an antelope."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_696", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/twirling_179.jpg", "positive_caption": ["A ballerina twirls in a ballet skirt."], "negative_caption": ["A ballet skirt twirls like a ballerina."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_697", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_48.jpg", "positive_caption": ["A person boards a train."], "negative_caption": ["A train boards a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_698", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_157.jpg", "positive_caption": ["A person boards a train."], "negative_caption": ["A train boards a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_699", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/serving_76.jpg", "positive_caption": ["A bartender serves ale."], "negative_caption": ["An ale serves the bartender."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_700", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/waving_113.jpg", "positive_caption": ["A mascot waves a flag."], "negative_caption": ["A flag waves over the mascot."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_701", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_113.jpg", "positive_caption": ["A soldier urinates on the ground."], "negative_caption": ["A ground urinates on a soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_702", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/competing_185.jpg", "positive_caption": ["A girl competes in gymnastics."], "negative_caption": ["The gymnastics compete with a girl."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_704", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spitting_111.jpg", "positive_caption": ["A man spits his drink."], "negative_caption": ["A drink spits at a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_705", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_263.jpg", "positive_caption": ["A man chases after a male child."], "negative_caption": ["A male child chases after a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_706", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interviewing_225.jpg", "positive_caption": ["A reporter interviews a policeman."], "negative_caption": ["A policeman interviews a reporter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_708", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_87.jpg", "positive_caption": ["A man works on a computer."], "negative_caption": ["A computer works like a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_709", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_189.jpg", "positive_caption": ["A man works on a computer."], "negative_caption": ["A computer works like a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_710", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_138.jpg", "positive_caption": ["An old man coaches a team."], "negative_caption": ["A team coaches like an old man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_711", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_20.jpg", "positive_caption": ["A teacher instructs a woman."], "negative_caption": ["A woman instructs a teacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_712", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_165.jpg", "positive_caption": ["A teacher instructs a woman."], "negative_caption": ["A woman instructs a teacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_713", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_72.jpg", "positive_caption": ["A man unveils a painting."], "negative_caption": ["A painting unveils of a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_714", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_193.jpg", "positive_caption": ["A man unveils a painting."], "negative_caption": ["A painting unveils of a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_715", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_150.jpg", "positive_caption": ["A woman sits in bed."], "negative_caption": ["A bed sits beside a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_716", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_162.jpg", "positive_caption": ["The people skip the jump rope."], "negative_caption": ["A jump rope skips the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_717", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_178.jpg", "positive_caption": ["The people skip the jump rope."], "negative_caption": ["A jump rope skips the people."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_718", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bulldozing_191.jpg", "positive_caption": ["A bulldozer bulldozes the soil."], "negative_caption": ["A soil bulldozes a bulldozer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_719", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_21.jpg", "positive_caption": ["A man chases after a woman."], "negative_caption": ["A woman chases after a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_720", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_43.jpg", "positive_caption": ["A man chases after a woman."], "negative_caption": ["A woman chases after a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_721", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/distracting_19.jpg", "positive_caption": ["A cellular telephone distracts the woman."], "negative_caption": ["A woman distracts from the telephone."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_722", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/grilling_84.jpg", "positive_caption": ["A person grills the meat."], "negative_caption": ["A meat grills a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_724", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_33.jpg", "positive_caption": ["A horse stumbles on the grass."], "negative_caption": ["The grass stumble a horse."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_725", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leaping_142.jpg", "positive_caption": ["A male child leaps onto a rock."], "negative_caption": ["A rock leaps at the male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_726", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skating_186.jpg", "positive_caption": ["A woman skates on an ice skate."], "negative_caption": ["An ice skate skates with a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_727", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/handcuffing_0.jpg", "positive_caption": ["A man handcuffs a woman."], "negative_caption": ["A woman handcuffs a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_728", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/handcuffing_40.jpg", "positive_caption": ["A man handcuffs a woman."], "negative_caption": ["A woman handcuffs a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_729", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/giggling_257.jpg", "positive_caption": ["A bride giggles at her groom."], "negative_caption": ["A groom giggles at his bride."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_730", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/releasing_100.jpg", "positive_caption": ["A man releases a bird."], "negative_caption": ["A bird releases a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_731", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/releasing_195.jpg", "positive_caption": ["A man releases a bird."], "negative_caption": ["A bird releases a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_732", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/detaining_110.jpg", "positive_caption": ["A soldier detains the man."], "negative_caption": ["A man detains a soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_733", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_2.jpg", "positive_caption": ["A woman admires such a man."], "negative_caption": ["A man admires such a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_734", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/launching_217.jpg", "positive_caption": ["A person launches a rocket."], "negative_caption": ["A rocket launches a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_736", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_136.jpg", "positive_caption": ["A mother complains to a doctor."], "negative_caption": ["A doctor complains to his mother."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_737", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_213.jpg", "positive_caption": ["A father scolds his child."], "negative_caption": ["A child scolds its father."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_738", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/preaching_79.jpg", "positive_caption": ["A preacher preaches people."], "negative_caption": ["The people preach the preacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_739", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/preaching_125.jpg", "positive_caption": ["A preacher preaches people."], "negative_caption": ["The people preach the preacher."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_740", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_39.jpg", "positive_caption": ["A ballplayer stumbles onto the ball field."], "negative_caption": ["A ball field stumbles on a ballplayer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_741", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bandaging_18.jpg", "positive_caption": ["A doctor bandages a woman."], "negative_caption": ["A woman bandages a doctor."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_742", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_133.jpg", "positive_caption": ["A man aims for a cellular telephone."], "negative_caption": ["A cellular telephone aims at the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_743", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/handcuffing_71.jpg", "positive_caption": ["A woman handcuffs a man."], "negative_caption": ["A man handcuffs a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_744", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_56.jpg", "positive_caption": ["A male child urinates against a bottle."], "negative_caption": ["A bottle urinates on a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_745", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/distracting_230.jpg", "positive_caption": ["A cellular telephone distracts the man."], "negative_caption": ["A man distracts a cellular telephone."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_746", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_58.jpg", "positive_caption": ["A man coaches a child."], "negative_caption": ["A child coaches a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_747", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_178.jpg", "positive_caption": ["A man coaches a child."], "negative_caption": ["A child coaches a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_748", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_274.jpg", "positive_caption": ["A man hunts a bird."], "negative_caption": ["A bird hunts a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_749", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_82.jpg", "positive_caption": ["A female child skips down a jump rope."], "negative_caption": ["A jump rope skips a female child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_750", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/parachuting_19.jpg", "positive_caption": ["A man parachutes from a parachute."], "negative_caption": ["A parachute parachutes on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_751", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_23.jpg", "positive_caption": ["A man pees the door."], "negative_caption": ["A door pees on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_752", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/dropping_247.jpg", "positive_caption": ["A paratrooper drops a parachute."], "negative_caption": ["A parachute drops on the paratrooper."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_753", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interrogating_110.jpg", "positive_caption": ["A soldier interrogates a man."], "negative_caption": ["A man interrogates a soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_754", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spitting_124.jpg", "positive_caption": ["A man spits out his beverage."], "negative_caption": ["A beverage spits a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_755", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baking_248.jpg", "positive_caption": ["A female child bakes the dough."], "negative_caption": ["A dough bakes for a female child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_756", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/helping_91.jpg", "positive_caption": ["A man helps a female child."], "negative_caption": ["A female child helps a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_757", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/brewing_85.jpg", "positive_caption": ["A man brews his coffee."], "negative_caption": ["A coffee brews for the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_758", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/brewing_181.jpg", "positive_caption": ["A man brews his coffee."], "negative_caption": ["A coffee brews for the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_759", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_210.jpg", "positive_caption": ["A person boards an airplane."], "negative_caption": ["An airplane boards a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_760", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_199.jpg", "positive_caption": ["A hunter hunts a bird."], "negative_caption": ["A bird hunts a hunter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_761", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sowing_137.jpg", "positive_caption": ["A man sows a bucket."], "negative_caption": ["A bucket sows a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_762", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_334.jpg", "positive_caption": ["A man sits in a chair."], "negative_caption": ["A chair sits beside the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_763", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_44.jpg", "positive_caption": ["A woman stumbles onto the ground."], "negative_caption": ["A ground stumbles behind the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_764", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_352.jpg", "positive_caption": ["A toddler chases after a cat."], "negative_caption": ["A cat chases after a toddler."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_765", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interrogating_108.jpg", "positive_caption": ["A soldier interrogates a private."], "negative_caption": ["A private interrogates a soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_766", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_34.jpg", "positive_caption": ["A mother scolds her daughter."], "negative_caption": ["A daughter scolds her mother."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_767", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/saluting_231.jpg", "positive_caption": ["A child salutes a soldier."], "negative_caption": ["A soldier salutes a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_768", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chewing_341.jpg", "positive_caption": ["A dog chews a bone."], "negative_caption": ["A bone chews like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_769", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_101.jpg", "positive_caption": ["A woman kneels behind a mat."], "negative_caption": ["A mat kneels beside the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_770", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_74.jpg", "positive_caption": ["A woman kneels behind a mat."], "negative_caption": ["A mat kneels beside the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_771", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_153.jpg", "positive_caption": ["A woman kneels behind a mat."], "negative_caption": ["A mat kneels beside the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_772", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_63.jpg", "positive_caption": ["A woman kneels on the mat."], "negative_caption": ["A mat kneels beside the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_773", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_20.jpg", "positive_caption": ["A woman kneels on the mat."], "negative_caption": ["A mat kneels beside the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_774", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_124.jpg", "positive_caption": ["A woman kneels on the mat."], "negative_caption": ["A mat kneels beside the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_775", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_152.jpg", "positive_caption": ["A male child pees on the ground."], "negative_caption": ["A ground pees on a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_776", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baptizing_90.jpg", "positive_caption": ["A priest baptizes a baby."], "negative_caption": ["A baby baptizes a priest."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_777", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baptizing_200.jpg", "positive_caption": ["A priest baptizes a baby."], "negative_caption": ["A baby baptizes a priest."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_778", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baptizing_201.jpg", "positive_caption": ["A priest baptizes a baby."], "negative_caption": ["A baby baptizes a priest."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_779", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/imitating_12.jpg", "positive_caption": ["A male child imitates such a woman."], "negative_caption": ["A woman imitates a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_780", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/fording_155.jpg", "positive_caption": ["A cowboy fords a horse."], "negative_caption": ["A horse fords for a cowboy."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_781", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_190.jpg", "positive_caption": ["A truck tows a motorcycle."], "negative_caption": ["A motorcycle tows a truck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_782", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/deflecting_97.jpg", "positive_caption": ["A combatant deflects the blow."], "negative_caption": ["A blow deflects the combatant."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_783", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/clawing_41.jpg", "positive_caption": ["A cat claws at the glass."], "negative_caption": ["The glass claw cat."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_784", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/operating_154.jpg", "positive_caption": ["A man operates from a control panel."], "negative_caption": ["A control panel operates the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_785", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_189.jpg", "positive_caption": ["A man complains to a doctor."], "negative_caption": ["A doctor complains to the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_786", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_114.jpg", "positive_caption": ["A man boards a ship."], "negative_caption": ["A ship boards with a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_787", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_45.jpg", "positive_caption": ["A husband scolds his wife."], "negative_caption": ["A wife scolds her husband."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_788", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/colliding_50.jpg", "positive_caption": ["A planet collides with Earth."], "negative_caption": ["A Earth collides with a planet."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_789", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/selling_132.jpg", "positive_caption": ["A woman sells her food."], "negative_caption": ["A food sells a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_790", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/selling_60.jpg", "positive_caption": ["A woman sells her food."], "negative_caption": ["A food sells a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_791", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_260.jpg", "positive_caption": ["A baby urinates on a toilet."], "negative_caption": ["A toilet urinates on a baby."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_792", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_258.jpg", "positive_caption": ["A hunter chases after a American bison."], "negative_caption": ["A American bison chases a hunter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_793", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_106.jpg", "positive_caption": ["A Transportation Security Administration frisks a man."], "negative_caption": ["A man frisks the Transportation Security Administration."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_795", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sniffing_223.jpg", "positive_caption": ["A puppy sniffs the grass."], "negative_caption": ["The grass sniff the puppy."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_796", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_32.jpg", "positive_caption": ["A man browses the card."], "negative_caption": ["A card browses the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_797", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/descending_171.jpg", "positive_caption": ["A woman descends down the stairs."], "negative_caption": ["The stairs descend behind the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_798", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_248.jpg", "positive_caption": ["A statue kneels on the floor."], "negative_caption": ["A floor kneels like a statue."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_799", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_216.jpg", "positive_caption": ["A man pees in the toilet."], "negative_caption": ["A toilet pees on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_801", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_283.jpg", "positive_caption": ["A child pees in the field."], "negative_caption": ["A field pees on a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_803", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_200.jpg", "positive_caption": ["A man instructs a drummer."], "negative_caption": ["A drummer instructs a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_804", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_217.jpg", "positive_caption": ["A duck sits in a nest."], "negative_caption": ["A nest sits like a duck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_805", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flapping_29.jpg", "positive_caption": ["A vulture flaps its wing."], "negative_caption": ["A wing flaps like a vulture."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_806", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gnawing_337.jpg", "positive_caption": ["A dog gnaws on a stick."], "negative_caption": ["A stick gnaws like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_807", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gnawing_394.jpg", "positive_caption": ["A dog gnaws on a stick."], "negative_caption": ["A stick gnaws like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_808", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_39.jpg", "positive_caption": ["An airplane lands in a field."], "negative_caption": ["A field lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_809", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/milking_226.jpg", "positive_caption": ["A woman milks a cow."], "negative_caption": ["A cow milks a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_810", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_31.jpg", "positive_caption": ["An old man complains to a doctor."], "negative_caption": ["A doctor complains to an old man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_811", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_108.jpg", "positive_caption": ["A man pees at a toilet."], "negative_caption": ["A toilet pees on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_812", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_200.jpg", "positive_caption": ["A man browses the apparel."], "negative_caption": ["An apparel browses the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_813", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_160.jpg", "positive_caption": ["A man kneels on the ground."], "negative_caption": ["A ground kneels over a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_814", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chewing_62.jpg", "positive_caption": ["A man chews a leaf."], "negative_caption": ["A leaf chews on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_815", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_233.jpg", "positive_caption": ["A woman browses the cheese."], "negative_caption": ["A cheese browses the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_816", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_217.jpg", "positive_caption": ["An airplane lands on a lawn."], "negative_caption": ["A lawn lands like an airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_817", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ducking_146.jpg", "positive_caption": ["A female child ducks through a door."], "negative_caption": ["A door ducks behind a female child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_818", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_24.jpg", "positive_caption": ["A hunter hunts an antelope."], "negative_caption": ["An antelope hunts a hunter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_819", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/checking_288.jpg", "positive_caption": ["A man checks the label."], "negative_caption": ["A label checks the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_820", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interrogating_58.jpg", "positive_caption": ["A detective interrogates an adolescent."], "negative_caption": ["An adolescent interrogates a detective."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_821", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_72.jpg", "positive_caption": ["A man aims for a rifle."], "negative_caption": ["A rifle aims at a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_822", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_123.jpg", "positive_caption": ["A man aims for a rifle."], "negative_caption": ["A rifle aims at a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_823", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/dialing_86.jpg", "positive_caption": ["A woman dials a cellular telephone."], "negative_caption": ["A cellular telephone dials a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_824", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chiseling_203.jpg", "positive_caption": ["A man chisels the limestone."], "negative_caption": ["A limestone chisels a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_825", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/grilling_54.jpg", "positive_caption": ["A man grills a chicken."], "negative_caption": ["A chicken grills a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_826", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/guarding_83.jpg", "positive_caption": ["A policeman guards a statue."], "negative_caption": ["A statue guards a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_827", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pedaling_260.jpg", "positive_caption": ["A woman pedals a bicycle."], "negative_caption": ["A bicycle pedals toward a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_828", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_265.jpg", "positive_caption": ["A lion hunts an animal."], "negative_caption": ["An animal hunts a lion."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_829", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_40.jpg", "positive_caption": ["A lion hunts an animal."], "negative_caption": ["An animal hunts a lion."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_830", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_128.jpg", "positive_caption": ["A woman chases after a male child."], "negative_caption": ["A male child chases after a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_831", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_42.jpg", "positive_caption": ["A man sits on a sofa."], "negative_caption": ["A sofa sits a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_832", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/selling_77.jpg", "positive_caption": ["A woman sells soap."], "negative_caption": ["A soap sells a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_833", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gnawing_42.jpg", "positive_caption": ["A mouse gnaws on a carrot."], "negative_caption": ["A carrot gnaws a mouse."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_834", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_153.jpg", "positive_caption": ["A male child urinates on a toilet."], "negative_caption": ["A toilet urinates on a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_835", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_69.jpg", "positive_caption": ["A policeman arrests such a man."], "negative_caption": ["A man arrests a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_836", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_14.jpg", "positive_caption": ["A policeman arrests such a man."], "negative_caption": ["A man arrests a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_837", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_60.jpg", "positive_caption": ["A policeman arrests such a man."], "negative_caption": ["A man arrests a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_838", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_213.jpg", "positive_caption": ["A policeman arrests such a man."], "negative_caption": ["A man arrests a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_839", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_111.jpg", "positive_caption": ["A policeman arrests such a man."], "negative_caption": ["A man arrests a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_840", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_146.jpg", "positive_caption": ["A coastguardsman boards a helicopter."], "negative_caption": ["A helicopter boards a coastguardsman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_841", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plowing_35.jpg", "positive_caption": ["A man plows over a tractor."], "negative_caption": ["A tractor plows over a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_842", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plowing_120.jpg", "positive_caption": ["A man plows over a tractor."], "negative_caption": ["A tractor plows over a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_843", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nagging_145.jpg", "positive_caption": ["A woman nags a man."], "negative_caption": ["A man nags a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_844", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nagging_64.jpg", "positive_caption": ["A woman nags a man."], "negative_caption": ["A man nags a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_845", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nagging_190.jpg", "positive_caption": ["A woman nags a man."], "negative_caption": ["A man nags a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_846", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nagging_63.jpg", "positive_caption": ["A woman nags a man."], "negative_caption": ["A man nags a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_847", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/apprehending_155.jpg", "positive_caption": ["A policeman apprehends a man."], "negative_caption": ["A man apprehends a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_848", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/apprehending_192.jpg", "positive_caption": ["A policeman apprehends a man."], "negative_caption": ["A man apprehends a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_849", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interviewing_202.jpg", "positive_caption": ["A reporter interviews a couple."], "negative_caption": ["A couple interviews with the reporter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_850", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baking_181.jpg", "positive_caption": ["A man bakes his bread."], "negative_caption": ["A bread bakes for a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_851", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_10.jpg", "positive_caption": ["A woman emerges from the swimming pool."], "negative_caption": ["A pool emerges behind a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_852", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_69.jpg", "positive_caption": ["A doctor communicates with an old woman."], "negative_caption": ["An old woman communicates with a doctor."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_853", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_14.jpg", "positive_caption": ["A ballplayer kneels at base."], "negative_caption": ["A base kneels before the ballplayer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_854", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_115.jpg", "positive_caption": ["A woman pees into a toilet."], "negative_caption": ["A toilet pees on a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_855", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_80.jpg", "positive_caption": ["A woman drives a tractor."], "negative_caption": ["A tractor drives by a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_856", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_150.jpg", "positive_caption": ["A policeman arrests a Santa Claus."], "negative_caption": ["The Santa Claus arrest the policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_857", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sucking_98.jpg", "positive_caption": ["A mosquito sucks at my skin."], "negative_caption": ["A skin sucks like a mosquito."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_858", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_187.jpg", "positive_caption": ["A male child skips down a jump rope."], "negative_caption": ["A jump rope skips a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_859", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_323.jpg", "positive_caption": ["A man sits against a wall."], "negative_caption": ["A wall sits behind a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_860", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/licking_291.jpg", "positive_caption": ["A cow licks its fur."], "negative_caption": ["A fur licks like a cow."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_861", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_67.jpg", "positive_caption": ["A female reads the label."], "negative_caption": ["A label reads : : female."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_863", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_181.jpg", "positive_caption": ["An oil tanker floats on water."], "negative_caption": ["A water floats in an oil tanker."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_864", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_76.jpg", "positive_caption": ["A man works with a desktop computer."], "negative_caption": ["A desktop computer works for a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_865", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leaping_269.jpg", "positive_caption": ["A woman leaps from the ground."], "negative_caption": ["A ground leaps toward the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_866", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_32.jpg", "positive_caption": ["A man burns his rubbish."], "negative_caption": ["A rubbish burns a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_867", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_139.jpg", "positive_caption": ["A hunter hunts a mammoth."], "negative_caption": ["A mammoth hunts a hunter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_868", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_86.jpg", "positive_caption": ["A horse stumbles onto the grass."], "negative_caption": ["The grass stumble a horse."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_870", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shopping_215.jpg", "positive_caption": ["A woman shops at a grocery store."], "negative_caption": ["A grocery store shops for a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_871", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_49.jpg", "positive_caption": ["A woman browses the apparel."], "negative_caption": ["An apparel browses the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_872", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_213.jpg", "positive_caption": ["A woman kneels on the floor."], "negative_caption": ["A floor kneels before a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_873", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_30.jpg", "positive_caption": ["A woman kneels on the floor."], "negative_caption": ["A floor kneels before a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_874", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punching_155.jpg", "positive_caption": ["A man punches a punching bag."], "negative_caption": ["A punching bag punches at a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_875", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_116.jpg", "positive_caption": ["A man boards an airplane."], "negative_caption": ["An airplane boards a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_876", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_77.jpg", "positive_caption": ["A hunter hunts a deer."], "negative_caption": ["The deer hunt a hunter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_877", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_31.jpg", "positive_caption": ["A hunter hunts a deer."], "negative_caption": ["The deer hunt a hunter."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_878", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_49.jpg", "positive_caption": ["A male child pees a toilet."], "negative_caption": ["A toilet pees on a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_880", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_141.jpg", "positive_caption": ["A horse stumbles on the racetrack."], "negative_caption": ["A racetrack stumbles over a horse."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_881", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/dialing_52.jpg", "positive_caption": ["A celebrity dials the telephone."], "negative_caption": ["A telephone dials for a celebrity."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_883", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kicking_37.jpg", "positive_caption": ["A young buck kicks a football."], "negative_caption": ["A football kicks a young buck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_884", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_343.jpg", "positive_caption": ["A cheetah chases a bird."], "negative_caption": ["A bird chases after a cheetah."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_885", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_121.jpg", "positive_caption": ["A serviceman arrests a woman."], "negative_caption": ["A woman arrests a serviceman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_887", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_55.jpg", "positive_caption": ["A businesswoman lectures with a colleague."], "negative_caption": ["A colleague lectures as a businesswoman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_889", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_338.jpg", "positive_caption": ["A log floats in the water."], "negative_caption": ["A water floats on a log."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_890", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_227.jpg", "positive_caption": ["A child sits at a desk."], "negative_caption": ["A desk sits like a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_891", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_20.jpg", "positive_caption": ["A boyfriend scolds his girlfriend."], "negative_caption": ["A girlfriend scolds her boyfriend."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_892", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_243.jpg", "positive_caption": ["A lion chases after an antelope."], "negative_caption": ["An antelope chases a lion."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_893", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_42.jpg", "positive_caption": ["A woman leads a parade."], "negative_caption": ["A parade leads to a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_895", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/destroying_64.jpg", "positive_caption": ["A bear destroys a cooler."], "negative_caption": ["A cooler destroys the bear."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_896", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_270.jpg", "positive_caption": ["A man trains with a colleague."], "negative_caption": ["A colleague trains a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_897", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/eating_336.jpg", "positive_caption": ["A male child eats a pizza."], "negative_caption": ["A pizza eats a male child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_898", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/applauding_279.jpg", "positive_caption": ["A girl applauds the speaker."], "negative_caption": ["A speaker applauds the girl."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_899", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_52.jpg", "positive_caption": ["A man stumbles onto the ground."], "negative_caption": ["A ground stumbles behind the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_900", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_42.jpg", "positive_caption": ["A man drives a car."], "negative_caption": ["A car drives by a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_901", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baptizing_73.jpg", "positive_caption": ["A curate baptizes a young buck."], "negative_caption": ["A young buck baptizes a curate."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_902", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_196.jpg", "positive_caption": ["A man packages food."], "negative_caption": ["A food packages man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_903", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/juggling_131.jpg", "positive_caption": ["A ballplayer juggles a baseball."], "negative_caption": ["A baseball juggles a ballplayer."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_904", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_47.jpg", "positive_caption": ["A dog urinates on the ground."], "negative_caption": ["A ground urinates on a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_905", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_46.jpg", "positive_caption": ["A dog urinates on the ground."], "negative_caption": ["A ground urinates on a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_906", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spitting_176.jpg", "positive_caption": ["A man spits out saliva."], "negative_caption": ["A saliva spits from a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_907", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spitting_168.jpg", "positive_caption": ["A man spits out saliva."], "negative_caption": ["A saliva spits from a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_908", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/brewing_67.jpg", "positive_caption": ["A man brews his food."], "negative_caption": ["A food brews for the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_910", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_188.jpg", "positive_caption": ["A tiger chases an antelope."], "negative_caption": ["An antelope chases a tiger."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_911", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_61.jpg", "positive_caption": ["A cat pees in the toilet."], "negative_caption": ["A toilet pees on a cat."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_912", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pouncing_170.jpg", "positive_caption": ["A leopard pounces on the ground."], "negative_caption": ["A ground pounces leopard."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_913", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gnawing_376.jpg", "positive_caption": ["An animal gnaws on a leaf."], "negative_caption": ["A leaf gnaws like an animal."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_914", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_28.jpg", "positive_caption": ["A boat floats on water."], "negative_caption": ["A water floats like a boat."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_916", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punching_28.jpg", "positive_caption": ["A woman punches a man."], "negative_caption": ["A man punches a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_917", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_204.jpg", "positive_caption": ["A car tows the trailer."], "negative_caption": ["A trailer tows the car."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_918", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_251.jpg", "positive_caption": ["A man urinates against a wall."], "negative_caption": ["A wall urinates on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_919", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_257.jpg", "positive_caption": ["A man urinates against a wall."], "negative_caption": ["A wall urinates on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_920", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_45.jpg", "positive_caption": ["A man urinates against a wall."], "negative_caption": ["A wall urinates on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_921", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_227.jpg", "positive_caption": ["A man urinates against a wall."], "negative_caption": ["A wall urinates on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_922", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_63.jpg", "positive_caption": ["A policeman frisks a man."], "negative_caption": ["A man frisks a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_923", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_117.jpg", "positive_caption": ["A policeman frisks a man."], "negative_caption": ["A man frisks a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_924", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_139.jpg", "positive_caption": ["A policeman frisks a man."], "negative_caption": ["A man frisks a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_925", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_20.jpg", "positive_caption": ["A policeman frisks a man."], "negative_caption": ["A man frisks a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_926", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_197.jpg", "positive_caption": ["A woman sits on a sofa."], "negative_caption": ["A sofa sits a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_927", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_69.jpg", "positive_caption": ["A wasp emerges from a nest."], "negative_caption": ["A nest emerges for the wasp."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_928", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/molding_6.jpg", "positive_caption": ["An artist molds the clay."], "negative_caption": ["A clay molds an artist."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_929", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_131.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["A runway lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_930", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_31.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["A runway lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_931", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_88.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["A runway lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_932", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_60.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["A runway lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_933", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_149.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["A runway lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_934", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_85.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["A runway lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_935", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_159.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["A runway lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_936", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_96.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["A runway lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_937", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_73.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["A runway lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_938", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_23.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["A runway lands the airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_939", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_233.jpg", "positive_caption": ["A policeman arrests an old man."], "negative_caption": ["An old man arrests a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_940", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/throwing_326.jpg", "positive_caption": ["A man throws a football."], "negative_caption": ["A football throws a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_943", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/apprehending_195.jpg", "positive_caption": ["A traffic cop apprehends a man."], "negative_caption": ["A man apprehends a traffic cop."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_944", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_154.jpg", "positive_caption": ["A woman works in sculpture."], "negative_caption": ["A sculpture works by a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_946", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/licking_225.jpg", "positive_caption": ["A dog licks its nose."], "negative_caption": ["A nose licks the dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_947", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/apprehending_36.jpg", "positive_caption": ["A policeman apprehends a male."], "negative_caption": ["A male apprehends a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_948", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_48.jpg", "positive_caption": ["A tiger chases a cow."], "negative_caption": ["A cow chases a tiger."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_949", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_165.jpg", "positive_caption": ["A soccer player stumbles onto the grass."], "negative_caption": ["The grass stumble a soccer player."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_950", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_222.jpg", "positive_caption": ["A man burns the debris."], "negative_caption": ["The debris burn the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_951", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/igniting_258.jpg", "positive_caption": ["A man ignites a cigarette."], "negative_caption": ["A cigarette ignites the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_952", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baking_113.jpg", "positive_caption": ["An old man bakes his bread."], "negative_caption": ["A bread bakes for an old man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_953", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_136.jpg", "positive_caption": ["A dog urinates in the grass."], "negative_caption": ["The grass urinate like a dog."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_954", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rotting_90.jpg", "positive_caption": ["A whale rots on shore."], "negative_caption": ["A shore rots like a whale."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_955", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_52.jpg", "positive_caption": ["A truck tows a trailer."], "negative_caption": ["A trailer tows a truck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_956", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_159.jpg", "positive_caption": ["A truck tows a trailer."], "negative_caption": ["A trailer tows a truck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_957", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_310.jpg", "positive_caption": ["A Orthodox Jew sits beside a sofa."], "negative_caption": ["A sofa sits an Orthodox Jew."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_958", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_140.jpg", "positive_caption": ["A man slips down the stairway."], "negative_caption": ["A stairway slips behind the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_959", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tripping_190.jpg", "positive_caption": ["A man trips through a stairwell."], "negative_caption": ["A stairwell trips a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_961", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/distracting_22.jpg", "positive_caption": ["A woman distracts a man."], "negative_caption": ["A man distracts a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_962", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_245.jpg", "positive_caption": ["A person burns the wood."], "negative_caption": ["A wood burns a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_963", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/smashing_239.jpg", "positive_caption": ["A man smashes a window."], "negative_caption": ["A window smashes into a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_964", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_113.jpg", "positive_caption": ["A truck tows a boat."], "negative_caption": ["A boat tows a truck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_965", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_51.jpg", "positive_caption": ["An insect emerges from a nest."], "negative_caption": ["A nest emerges for the insect."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_966", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/subduing_50.jpg", "positive_caption": ["A policeman subdues an intruder."], "negative_caption": ["An intruder subdues a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_969", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_60.jpg", "positive_caption": ["A truck tows a tractor."], "negative_caption": ["A tractor tows a truck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_970", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/autographing_194.jpg", "positive_caption": ["A man autographes a book."], "negative_caption": ["A book autographes a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_971", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_345.jpg", "positive_caption": ["A motorcyclist chases after a man."], "negative_caption": ["A man chases after a motorcyclist."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_973", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pouncing_185.jpg", "positive_caption": ["A cheetah pounces prey."], "negative_caption": ["A prey pounces on the cheetah."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_974", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/restraining_120.jpg", "positive_caption": ["A policeman restrains a man."], "negative_caption": ["A man restrains a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_975", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_165.jpg", "positive_caption": ["A man kneels behind a mat."], "negative_caption": ["A mat kneels beside the man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_976", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lighting_113.jpg", "positive_caption": ["A man lights up a cigarette."], "negative_caption": ["A cigarette lights up a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_977", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_175.jpg", "positive_caption": ["A man stumbles into the stairs."], "negative_caption": ["The stairs stumble over a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_978", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_176.jpg", "positive_caption": ["A truck tows a car."], "negative_caption": ["A car tows the truck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_979", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_157.jpg", "positive_caption": ["A truck tows a car."], "negative_caption": ["A car tows the truck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_980", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hauling_138.jpg", "positive_caption": ["A truck hauls a log."], "negative_caption": ["A log hauls the truck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_981", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_34.jpg", "positive_caption": ["A leopard hunts a crocodile."], "negative_caption": ["A crocodile hunts a leopard."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_982", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/taxiing_268.jpg", "positive_caption": ["An airplane taxis on a runway."], "negative_caption": ["A runway taxis an airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_983", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/taxiing_246.jpg", "positive_caption": ["An airplane taxis on a runway."], "negative_caption": ["A runway taxis an airplane."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_984", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/videotaping_45.jpg", "positive_caption": ["A man videotapes the fencing."], "negative_caption": ["A fencing videotapes a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_985", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/subduing_150.jpg", "positive_caption": ["A policeman subdues a man."], "negative_caption": ["A man subdues a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_986", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/subduing_124.jpg", "positive_caption": ["A policeman subdues a man."], "negative_caption": ["A man subdues a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_987", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/subduing_125.jpg", "positive_caption": ["A policeman subdues a man."], "negative_caption": ["A man subdues a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_988", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/subduing_201.jpg", "positive_caption": ["A policeman subdues a man."], "negative_caption": ["A man subdues a policeman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_989", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_182.jpg", "positive_caption": ["A man urinates on a toilet."], "negative_caption": ["A toilet urinates on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_992", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ignoring_209.jpg", "positive_caption": ["A man ignores a woman."], "negative_caption": ["A woman ignores a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_994", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/smashing_119.jpg", "positive_caption": ["A woman smashes a wall."], "negative_caption": ["A wall smashes into the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_995", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/glaring_150.jpg", "positive_caption": ["A woman glares at the man."], "negative_caption": ["A man glares at a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_996", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/releasing_204.jpg", "positive_caption": ["A man releases a turtle."], "negative_caption": ["A turtle releases a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_997", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/imitating_87.jpg", "positive_caption": ["A woman imitates the statue."], "negative_caption": ["A statue imitates a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_999", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_195.jpg", "positive_caption": ["A man urinates against a fence."], "negative_caption": ["A fence urinates on a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1001", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_85.jpg", "positive_caption": ["A woman drives a car."], "negative_caption": ["A car drives by a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1002", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_17.jpg", "positive_caption": ["A woman drives a car."], "negative_caption": ["A car drives by a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1003", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_19.jpg", "positive_caption": ["A woman drives a car."], "negative_caption": ["A car drives by a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1004", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_257.jpg", "positive_caption": ["A woman drives a car."], "negative_caption": ["A car drives by a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1005", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_179.jpg", "positive_caption": ["A woman drives a car."], "negative_caption": ["A car drives by a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1006", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_29.jpg", "positive_caption": ["A man stumbles down the stairs."], "negative_caption": ["The stairs stumble over a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1008", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_154.jpg", "positive_caption": ["An agent frisks a man."], "negative_caption": ["A man frisks an agent."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1009", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_15.jpg", "positive_caption": ["A man drives a motorcycle."], "negative_caption": ["A motorcycle drives by a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1010", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_303.jpg", "positive_caption": ["A person presses an alarm."], "negative_caption": ["An alarm presses on a person."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1011", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_162.jpg", "positive_caption": ["A police matron frisks the man."], "negative_caption": ["A man frisks police."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1013", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/moistening_79.jpg", "positive_caption": ["A woman moistens the sculpture."], "negative_caption": ["A sculpture moistens like a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1014", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pulling_192.jpg", "positive_caption": ["A truck pulls a boat."], "negative_caption": ["A boat pulls the truck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1015", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/painting_152.jpg", "positive_caption": ["A woman paints a painting."], "negative_caption": ["A painting paints a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1016", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stretching_136.jpg", "positive_caption": ["An old man stretches a leg."], "negative_caption": ["A leg stretches like a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1017", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_330.jpg", "positive_caption": ["A man admires a painting."], "negative_caption": ["A painting admires such a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1018", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/folding_258.jpg", "positive_caption": ["A child folds the paper."], "negative_caption": ["A paper folds like a child."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1019", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_133.jpg", "positive_caption": ["A girl stumbles into the stairs."], "negative_caption": ["The stairs stumble toward the girl."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1020", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_180.jpg", "positive_caption": ["A space shuttle lands on a runway."], "negative_caption": ["A runway lands on the space shuttle."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1021", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/subduing_22.jpg", "positive_caption": ["A soldier subdues a man."], "negative_caption": ["A man subdues a soldier."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1022", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spitting_42.jpg", "positive_caption": ["A snake spits venom."], "negative_caption": ["A venom spits at the snake."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1023", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_186.jpg", "positive_caption": ["A woman drives a truck."], "negative_caption": ["A truck drives toward the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1024", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spitting_13.jpg", "positive_caption": ["A man spits blood."], "negative_caption": ["A blood spits from a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1025", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/videotaping_73.jpg", "positive_caption": ["A man videotapes a woman."], "negative_caption": ["A woman videotapes a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1026", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chewing_360.jpg", "positive_caption": ["A woman chews food."], "negative_caption": ["A food chews like a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1027", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_238.jpg", "positive_caption": ["A woman browses a magazine."], "negative_caption": ["A magazine browses on a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1028", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/recovering_130.jpg", "positive_caption": ["A woman recovers from injury."], "negative_caption": ["An injury recovers a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1029", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_190.jpg", "positive_caption": ["A woman drives a van."], "negative_caption": ["A van drives the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1030", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pulling_37.jpg", "positive_caption": ["A truck pulls a trailer."], "negative_caption": ["A trailer pulls a truck."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1031", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gnawing_359.jpg", "positive_caption": ["A baby gnaws in a crib."], "negative_caption": ["A crib gnaws a baby."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1032", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_49.jpg", "positive_caption": ["A woman stumbles down the stairs."], "negative_caption": ["The stairs stumble toward a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1033", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gnawing_122.jpg", "positive_caption": ["A girl gnaws meat."], "negative_caption": ["A meat gnaws girl."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1034", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/recovering_160.jpg", "positive_caption": ["A woman recovers from the childbirth."], "negative_caption": ["A childbirth recovers the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1035", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/decorating_42.jpg", "positive_caption": ["A woman decorates the wall."], "negative_caption": ["A wall decorates the woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1036", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_253.jpg", "positive_caption": ["A man drives a trailer truck."], "negative_caption": ["A trailer truck drives past a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1037", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/cooking_66.jpg", "positive_caption": ["A man cooks a turkey."], "negative_caption": ["A turkey cooks a man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1038", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_228.jpg", "positive_caption": ["A woman sits at the piano."], "negative_caption": ["A piano sits beside a woman."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1039", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gnawing_178.jpg", "positive_caption": ["A man gnaws meat."], "negative_caption": ["A meat gnaws man."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1040", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rotting_182.jpg", "positive_caption": ["A hamburger rots the table."], "negative_caption": ["A table rots like a hamburger."], "original_file_name": "actant-swap", "dataset": "SWiG", "key": "actions_test_1041", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/exercising_255.jpg", "positive_caption": ["A man exercises his torso."], "negative_caption": ["A man lifts his torso."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_0", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/turning_172.jpg", "positive_caption": ["A male child turns his head."], "negative_caption": ["A male child lifts his head."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_1", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/displaying_251.jpg", "positive_caption": ["A man displays a certificate."], "negative_caption": ["A man carries a certificate."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_3", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_139.jpg", "positive_caption": ["The people unveil the prize."], "negative_caption": ["The people offer the prize."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_4", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_74.jpg", "positive_caption": ["A man unveils a statue."], "negative_caption": ["A man carves a statue."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_5", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sucking_143.jpg", "positive_caption": ["A woman sucks on a candy cane."], "negative_caption": ["A woman sits on a candy cane."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_6", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/clapping_56.jpg", "positive_caption": ["A toddler claps out a hand."], "negative_caption": ["A toddler stretches out a hand."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_7", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/parachuting_100.jpg", "positive_caption": ["The people parachute into the parachute."], "negative_caption": ["The people climb into the parachute."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_8", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_114.jpg", "positive_caption": ["A girl reads a book."], "negative_caption": ["A girl writes a book."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_9", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_5.jpg", "positive_caption": ["A dog pees on a fireplug."], "negative_caption": ["A dog sits on a fireplug."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_11", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arching_231.jpg", "positive_caption": ["A man arches his back."], "negative_caption": ["A man turns his back."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_12", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rehabilitating_199.jpg", "positive_caption": ["A woman rehabilitates a person."], "negative_caption": ["A woman helps a person."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_13", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_199.jpg", "positive_caption": ["The people package the food."], "negative_caption": ["The people eat the food."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_14", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/paying_50.jpg", "positive_caption": ["A person pays another person."], "negative_caption": ["A person helps another person."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_15", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nuzzling_181.jpg", "positive_caption": ["A horse nuzzles a horse."], "negative_caption": ["A horse rides a horse."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_16", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/counting_103.jpg", "positive_caption": ["A person counts money."], "negative_caption": ["A person pays money."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_17", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_35.jpg", "positive_caption": ["The people disembark from ship."], "negative_caption": ["The people emerge from ship."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_22", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lacing_36.jpg", "positive_caption": ["A woman laces up a gym shoe."], "negative_caption": ["A woman pulls up a gym shoe."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_24", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tackling_110.jpg", "positive_caption": ["A person tackles another person."], "negative_caption": ["A person eats another person."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_25", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/riding_24.jpg", "positive_caption": ["A man rides the raft."], "negative_caption": ["A man boards the raft."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_26", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nuzzling_264.jpg", "positive_caption": ["A wife nuzzles her husband."], "negative_caption": ["A wife serves her husband."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_28", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneading_7.jpg", "positive_caption": ["A woman kneads dough."], "negative_caption": ["A woman bakes dough."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_29", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_135.jpg", "positive_caption": ["The people disembark an airplane."], "negative_caption": ["The people board an airplane."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_30", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/applauding_36.jpg", "positive_caption": ["A guest applauds a speaker."], "negative_caption": ["A guest provides a speaker."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_31", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/inflating_144.jpg", "positive_caption": ["A man inflates his mouth."], "negative_caption": ["A man drops his mouth."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_32", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_259.jpg", "positive_caption": ["The people row in a boat."], "negative_caption": ["The people sit in a boat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_33", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/carving_74.jpg", "positive_caption": ["A person carves wood."], "negative_caption": ["A person burns wood."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_34", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/talking_247.jpg", "positive_caption": ["A man talks to a person."], "negative_caption": ["A man leads to a person."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_35", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_10.jpg", "positive_caption": ["A woman reads through a book."], "negative_caption": ["A woman flips through a book."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_36", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_24.jpg", "positive_caption": ["A young buck encourages a girl."], "negative_caption": ["A young buck chases a girl."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_40", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/talking_258.jpg", "positive_caption": ["A man talks to a man."], "negative_caption": ["A man calls to a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_41", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hurling_20.jpg", "positive_caption": ["A man hurls the ball."], "negative_caption": ["A man chases the ball."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_42", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_155.jpg", "positive_caption": ["A dog sits beside a dog."], "negative_caption": ["A dog kneels beside a dog."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_43", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_235.jpg", "positive_caption": ["A woman bites her shoe."], "negative_caption": ["A woman examines her shoe."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_44", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/heaving_42.jpg", "positive_caption": ["A man heaves a rock."], "negative_caption": ["A man rides a rock."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_45", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_119.jpg", "positive_caption": ["An old man reads through a book."], "negative_caption": ["An old man turns through a book."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_47", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/falling_136.jpg", "positive_caption": ["A sprinter falls off a racetrack."], "negative_caption": ["A sprinter pulls off a racetrack."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_48", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_34.jpg", "positive_caption": ["The people disembark from a ferry."], "negative_caption": ["The people board a ferry."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_49", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_240.jpg", "positive_caption": ["A person admires a woman."], "negative_caption": ["A person calls a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_50", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/smelling_2.jpg", "positive_caption": ["A male child smells the flow."], "negative_caption": ["A male child breaks the flow."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_51", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/whistling_112.jpg", "positive_caption": ["An old man whistles with a finger."], "negative_caption": ["An old man pokes with a finger."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_52", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/grilling_61.jpg", "positive_caption": ["A person grills a chicken."], "negative_caption": ["A person calls a chicken."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_53", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_98.jpg", "positive_caption": ["A child encourages such a child."], "negative_caption": ["A child calls such a child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_54", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_34.jpg", "positive_caption": ["A man teaches a woman."], "negative_caption": ["A man chases a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_55", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_145.jpg", "positive_caption": ["A man burns a card game."], "negative_caption": ["A man calls a card game."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_56", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flexing_38.jpg", "positive_caption": ["A man flexes his biceps."], "negative_caption": ["A man rubs his biceps."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_57", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_98.jpg", "positive_caption": ["A woman unveils the brass."], "negative_caption": ["A woman bites the brass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_58", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_115.jpg", "positive_caption": ["A horse nips a horse."], "negative_caption": ["A horse drives a horse."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_59", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sniffing_185.jpg", "positive_caption": ["A dog sniffs the ground."], "negative_caption": ["A dog bites the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_60", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_77.jpg", "positive_caption": ["A woman slips into the ground."], "negative_caption": ["A woman presses into the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_61", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wrinkling_117.jpg", "positive_caption": ["A woman wrinkles her face."], "negative_caption": ["A woman turns her face."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_62", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_110.jpg", "positive_caption": ["The people disembark a raft."], "negative_caption": ["The people assemble a raft."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_63", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_154.jpg", "positive_caption": ["The people unveil a painting."], "negative_caption": ["The people paint a painting."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_64", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_19.jpg", "positive_caption": ["A parent encourages such a girl."], "negative_caption": ["A parent teaches such a girl."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_65", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_172.jpg", "positive_caption": ["A parent scolds a child."], "negative_caption": ["A parent teaches a child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_66", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lacing_64.jpg", "positive_caption": ["A man laces up his shoe."], "negative_caption": ["A man kicks up his shoe."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_67", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/heaving_86.jpg", "positive_caption": ["A man heaves a dumbbell."], "negative_caption": ["A man swings a dumbbell."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_69", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flexing_148.jpg", "positive_caption": ["A man flexes his torso."], "negative_caption": ["A man stretches his torso."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_70", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_152.jpg", "positive_caption": ["A man works the table."], "negative_caption": ["A man circles the table."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_71", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/confronting_51.jpg", "positive_caption": ["A goat confronts a goat."], "negative_caption": ["A goat bites a goat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_72", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_131.jpg", "positive_caption": ["A man encourages a child."], "negative_caption": ["A man chases a child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_73", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/speaking_41.jpg", "positive_caption": ["A woman speaks in person."], "negative_caption": ["A woman works in person."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_74", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gambling_253.jpg", "positive_caption": ["A man gambles on a chip."], "negative_caption": ["A man chews on a chip."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_75", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/paying_168.jpg", "positive_caption": ["A man pays a cashier."], "negative_caption": ["A man turns a cashier."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_76", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flipping_208.jpg", "positive_caption": ["The people flip a boat."], "negative_caption": ["The people board a boat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_77", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunching_21.jpg", "positive_caption": ["A man hunches over his chess set."], "negative_caption": ["A man knocks over his chess set."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_78", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/socializing_108.jpg", "positive_caption": ["A dog socializes with a dog."], "negative_caption": ["A dog interviews with a dog."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_80", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_41.jpg", "positive_caption": ["A woman teaches a child."], "negative_caption": ["A woman leads a child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_81", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/turning_102.jpg", "positive_caption": ["A soccer player turns his head."], "negative_caption": ["A soccer player ducks his head."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_82", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_82.jpg", "positive_caption": ["A man presses the plunger."], "negative_caption": ["A man punches the plunger."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_83", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shelling_55.jpg", "positive_caption": ["A chef shells up an oyster."], "negative_caption": ["A chef lights up an oyster."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_84", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_47.jpg", "positive_caption": ["The people commute by bicycle."], "negative_caption": ["The people communicate by bicycle."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_87", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/begging_156.jpg", "positive_caption": ["A beaver begs a woman."], "negative_caption": ["A beaver chases a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_88", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spanking_55.jpg", "positive_caption": ["A woman spanks her daughter."], "negative_caption": ["A woman embraces her daughter."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_89", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneading_231.jpg", "positive_caption": ["A man kneads dough."], "negative_caption": ["A man bakes dough."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_90", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_328.jpg", "positive_caption": ["A dog tugs a rope."], "negative_caption": ["A dog throws a rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_94", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chiseling_6.jpg", "positive_caption": ["A man chisels a rock."], "negative_caption": ["A man butts a rock."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_95", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_110.jpg", "positive_caption": ["A father scolds a male child."], "negative_caption": ["A father teaches a male child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_96", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/restraining_144.jpg", "positive_caption": ["A person restrains another person."], "negative_caption": ["A person destroys another person."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_97", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/butting_237.jpg", "positive_caption": ["A man butts a woman."], "negative_caption": ["A man chases a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_98", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_14.jpg", "positive_caption": ["A person works with art."], "negative_caption": ["A person confronts with art."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_100", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_29.jpg", "positive_caption": ["A person tugs a power cord."], "negative_caption": ["A person opers a power cord."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_101", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tackling_130.jpg", "positive_caption": ["A football player tackles a running back."], "negative_caption": ["A football player throws a running back."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_102", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wrinkling_31.jpg", "positive_caption": ["A girl wrinkles her nose."], "negative_caption": ["A girl twists her nose."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_103", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arching_3.jpg", "positive_caption": ["A cat arches over the spinal column."], "negative_caption": ["A cat leaps over the spinal column."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_104", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_227.jpg", "positive_caption": ["A man calls for a land line."], "negative_caption": ["A man works for a land line."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_105", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunching_176.jpg", "positive_caption": ["A man hunches on a golf club."], "negative_caption": ["A man swings on a golf club."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_106", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kicking_168.jpg", "positive_caption": ["A man kicks a soccer ball."], "negative_caption": ["A man chases a soccer ball."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_107", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_181.jpg", "positive_caption": ["A man encourages a woman."], "negative_caption": ["A man chases a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_109", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/giggling_187.jpg", "positive_caption": ["A woman giggles with a man."], "negative_caption": ["A woman sits with a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_110", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/asking_51.jpg", "positive_caption": ["A young buck asks for a girl."], "negative_caption": ["A young buck falls for a girl."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_111", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_35.jpg", "positive_caption": ["The people commute by train."], "negative_caption": ["The people board by train."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_112", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shelving_223.jpg", "positive_caption": ["A man shelves a bottle."], "negative_caption": ["A man pushes a bottle."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_114", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wrinkling_12.jpg", "positive_caption": ["A male child wrinkles his brow."], "negative_caption": ["A male child arches his brow."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_115", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_177.jpg", "positive_caption": ["A couple forages for a plant."], "negative_caption": ["A couple falls for a plant."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_117", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/paying_206.jpg", "positive_caption": ["A customer pays a cashier."], "negative_caption": ["A customer drives a cashier."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_118", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_17.jpg", "positive_caption": ["A man forages for a flower."], "negative_caption": ["A man asks for a flower."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_119", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_183.jpg", "positive_caption": ["A man sits on a roof."], "negative_caption": ["A man lands on a roof."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_120", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ducking_52.jpg", "positive_caption": ["A man ducks for a punch."], "negative_caption": ["A man asks for a punch."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_121", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_223.jpg", "positive_caption": ["A farmer works on picking."], "negative_caption": ["A farmer sits on picking."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_122", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/typing_116.jpg", "positive_caption": ["A woman types with a keyboard."], "negative_caption": ["A woman sits with a keyboard."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_123", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tackling_9.jpg", "positive_caption": ["A football player tackles all the opposition."], "negative_caption": ["A football player reads all the opposition."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_124", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/waving_199.jpg", "positive_caption": ["The people wave a flag."], "negative_caption": ["The people ask a flag."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_125", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_2.jpg", "positive_caption": ["A man tills up a cultivator."], "negative_caption": ["A man kicks up a cultivator."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_126", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sowing_0.jpg", "positive_caption": ["A farmer sows his hand."], "negative_caption": ["A farmer waves his hand."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_128", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_372.jpg", "positive_caption": ["A woman admires a baby."], "negative_caption": ["A woman kicks a baby."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_129", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/carving_5.jpg", "positive_caption": ["A man carves from limestone."], "negative_caption": ["A man emerges from limestone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_130", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wrinkling_25.jpg", "positive_caption": ["A male child wrinkles his nose."], "negative_caption": ["A male child pushes his nose."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_132", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wagging_64.jpg", "positive_caption": ["A dog wags a tail."], "negative_caption": ["A dog displays a tail."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_135", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rehabilitating_94.jpg", "positive_caption": ["A woman rehabilitates her leg."], "negative_caption": ["A woman kicks her leg."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_136", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sowing_154.jpg", "positive_caption": ["A person sows a finger."], "negative_caption": ["A person waves a finger."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_138", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lacing_178.jpg", "positive_caption": ["A man laces up a gym shoe."], "negative_caption": ["A man buttons up a gym shoe."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_139", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_59.jpg", "positive_caption": ["A congressman reads Isaiah."], "negative_caption": ["A congressman asks Isaiah."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_141", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_152.jpg", "positive_caption": ["A person admires a person."], "negative_caption": ["A person leads a person."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_142", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_49.jpg", "positive_caption": ["The people commute by bus."], "negative_caption": ["The people work by bus."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_143", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/encouraging_88.jpg", "positive_caption": ["A woman encourages a young toddler."], "negative_caption": ["A woman chases a young toddler."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_144", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_202.jpg", "positive_caption": ["A woman teaches people."], "negative_caption": ["A woman reads people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_146", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/descending_98.jpg", "positive_caption": ["The people descend on foot."], "negative_caption": ["The people work on foot."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_147", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_301.jpg", "positive_caption": ["The people pee on the grass."], "negative_caption": ["The people sit on the grass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_148", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/examining_246.jpg", "positive_caption": ["A man examines the ground."], "negative_caption": ["A man sniffs the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_149", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_233.jpg", "positive_caption": ["The people work in a garden."], "negative_caption": ["The people sit in a garden."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_151", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_67.jpg", "positive_caption": ["A mother reassures her daughter."], "negative_caption": ["A mother teaches her daughter."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_152", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shouting_344.jpg", "positive_caption": ["A man shouts at another man."], "negative_caption": ["A man stares at another man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_154", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/applauding_173.jpg", "positive_caption": ["A person applauds the President of the United States."], "negative_caption": ["A person counts the President of the United States."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_156", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_302.jpg", "positive_caption": ["A man bites into a branch."], "negative_caption": ["A man carves into a branch."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_157", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_239.jpg", "positive_caption": ["The people camp in a tent."], "negative_caption": ["The people sit in a tent."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_159", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/buttoning_129.jpg", "positive_caption": ["A man buttons up a sweater."], "negative_caption": ["A man folds up a sweater."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_160", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wringing_15.jpg", "positive_caption": ["A woman wrings fabric."], "negative_caption": ["A woman sews fabric."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_161", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gardening_114.jpg", "positive_caption": ["A person gardens a spade."], "negative_caption": ["A person bites a spade."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_162", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_80.jpg", "positive_caption": ["A man scolds a man."], "negative_caption": ["A man butts a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_163", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_203.jpg", "positive_caption": ["A woman scolds a male child."], "negative_caption": ["A woman teaches a male child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_164", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_87.jpg", "positive_caption": ["A boatman disembarks from the ship."], "negative_caption": ["A boatman emerges from the ship."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_165", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_118.jpg", "positive_caption": ["A mother reassures her child."], "negative_caption": ["A mother guards her child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_167", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_123.jpg", "positive_caption": ["A coach coaches a team."], "negative_caption": ["A coach leads a team."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_168", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_168.jpg", "positive_caption": ["A man sits on a rock."], "negative_caption": ["A man slips on a rock."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_169", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/puckering_119.jpg", "positive_caption": ["A man puckers his lip."], "negative_caption": ["A man bites his lip."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_170", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_172.jpg", "positive_caption": ["A woman teaches a female child."], "negative_caption": ["A woman provides a female child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_171", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_100.jpg", "positive_caption": ["A woman browses my shirt."], "negative_caption": ["A woman buttons my shirt."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_173", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_35.jpg", "positive_caption": ["A man slips to the ground."], "negative_caption": ["A man leaps to the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_174", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ramming_156.jpg", "positive_caption": ["A train rams the car."], "negative_caption": ["A train tows the car."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_175", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lifting_110.jpg", "positive_caption": ["A man lifts weight."], "negative_caption": ["A man measurs weight."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_176", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nipping_40.jpg", "positive_caption": ["A puppy nips a dog."], "negative_caption": ["A puppy chases a dog."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_177", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/dialing_63.jpg", "positive_caption": ["A person dials a telephone."], "negative_caption": ["A person speaks a telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_178", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stretching_291.jpg", "positive_caption": ["A person stretches their neck."], "negative_caption": ["A person checks their neck."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_179", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chiseling_221.jpg", "positive_caption": ["A man chisels a statue."], "negative_caption": ["A man chases a statue."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_181", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/buttoning_51.jpg", "positive_caption": ["A woman buttons her coat."], "negative_caption": ["A woman folds her coat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_183", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_116.jpg", "positive_caption": ["A man lectures people."], "negative_caption": ["A man reads people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_185", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_180.jpg", "positive_caption": ["A man trains people."], "negative_caption": ["A man sells people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_186", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/teaching_7.jpg", "positive_caption": ["A coach teaches a boxer."], "negative_caption": ["A coach works a boxer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_187", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_30.jpg", "positive_caption": ["A girl scolds a male child."], "negative_caption": ["A girl guards a male child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_188", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_194.jpg", "positive_caption": ["A football player punts a football."], "negative_caption": ["A football player drives a football."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_189", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_147.jpg", "positive_caption": ["A woman scolds another woman."], "negative_caption": ["A woman chases another woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_190", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/educating_58.jpg", "positive_caption": ["A man educates a student."], "negative_caption": ["A man butts a student."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_191", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneading_209.jpg", "positive_caption": ["A person kneads the meat."], "negative_caption": ["A person sells the meat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_192", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/folding_204.jpg", "positive_caption": ["A person folds a sheet."], "negative_caption": ["A person reads a sheet."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_193", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/counting_133.jpg", "positive_caption": ["A person counts a bill."], "negative_caption": ["A person pays a bill."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_194", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/speaking_84.jpg", "positive_caption": ["A baby speaks on a telephone."], "negative_caption": ["A baby sits on a telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_195", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/offering_207.jpg", "positive_caption": ["A man offers me a hand."], "negative_caption": ["A man asks me a hand."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_196", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pouncing_246.jpg", "positive_caption": ["A lion pounces upon a lion."], "negative_caption": ["A lion sits upon a lion."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_197", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_173.jpg", "positive_caption": ["A woman works on paper."], "negative_caption": ["A woman types on paper."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_198", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/typing_179.jpg", "positive_caption": ["A man types a laptop."], "negative_caption": ["A man reads a laptop."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_199", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_257.jpg", "positive_caption": ["A woman trains people."], "negative_caption": ["A woman sells people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_200", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_52.jpg", "positive_caption": ["A soccer player reassures the goalkeeper."], "negative_caption": ["A soccer player works the goalkeeper."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_201", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_153.jpg", "positive_caption": ["A woman aims a shotgun."], "negative_caption": ["A woman hauls a shotgun."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_202", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_37.jpg", "positive_caption": ["A trainer trains an elephant."], "negative_caption": ["A trainer drives an elephant."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_203", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skating_27.jpg", "positive_caption": ["A person skates on an ice skate."], "negative_caption": ["A person lands on an ice skate."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_204", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_90.jpg", "positive_caption": ["A woman coaches people."], "negative_caption": ["A woman reads people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_208", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_37.jpg", "positive_caption": ["The people row in a canoe."], "negative_caption": ["The people land in a canoe."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_209", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/climbing_191.jpg", "positive_caption": ["A figure climbs the stairs."], "negative_caption": ["A figure descends the stairs."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_210", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_102.jpg", "positive_caption": ["A man forages a berry."], "negative_caption": ["A man bites a berry."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_211", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tackling_109.jpg", "positive_caption": ["An athlete tackles the opposition."], "negative_caption": ["An athlete coaches the opposition."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_212", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_54.jpg", "positive_caption": ["A man tugs a bandage."], "negative_caption": ["A man ties a bandage."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_213", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_64.jpg", "positive_caption": ["A man slips into the ground."], "negative_caption": ["A man smashes into the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_214", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sniffing_62.jpg", "positive_caption": ["A dog sniffs the grass."], "negative_caption": ["A dog bites the grass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_215", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_130.jpg", "positive_caption": ["A tennis player slips into the ground."], "negative_caption": ["A tennis player smashes into the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_216", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ducking_71.jpg", "positive_caption": ["A boxer ducks for a punch."], "negative_caption": ["A boxer aims for a punch."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_218", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_80.jpg", "positive_caption": ["A person aims a gun."], "negative_caption": ["A person chases a gun."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_219", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/asking_129.jpg", "positive_caption": ["A nurse asks a patient."], "negative_caption": ["A nurse guards a patient."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_221", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camouflaging_240.jpg", "positive_caption": ["A hunter camouflages the vegetation."], "negative_caption": ["A hunter hunts the vegetation."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_223", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_135.jpg", "positive_caption": ["A woman leads the people."], "negative_caption": ["A woman pays the people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_224", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/talking_282.jpg", "positive_caption": ["A woman talks to people."], "negative_caption": ["A woman complains to people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_226", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nuzzling_4.jpg", "positive_caption": ["A mother nuzzles her baby."], "negative_caption": ["A mother ignores her baby."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_228", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_131.jpg", "positive_caption": ["A soccer player slips to the ground."], "negative_caption": ["A soccer player descends to the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_229", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_210.jpg", "positive_caption": ["A colleague works on an undertaking."], "negative_caption": ["A colleague counts on an undertaking."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_230", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_59.jpg", "positive_caption": ["A man coaches a man."], "negative_caption": ["A man chases a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_232", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_61.jpg", "positive_caption": ["A man unveils the display."], "negative_caption": ["A man adjusts the display."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_234", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/speaking_241.jpg", "positive_caption": ["A woman speaks to a female child."], "negative_caption": ["A woman educates to a female child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_235", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kicking_339.jpg", "positive_caption": ["A man kicks a sandbag."], "negative_caption": ["A man swings a sandbag."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_236", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/blocking_273.jpg", "positive_caption": ["A gate blocks the truck."], "negative_caption": ["A gate drives the truck."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_237", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_171.jpg", "positive_caption": ["A parent scolds the lass."], "negative_caption": ["A parent ignores the lass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_238", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shopping_20.jpg", "positive_caption": ["A woman shops for an apple."], "negative_caption": ["A woman asks for an apple."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_240", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tripping_3.jpg", "positive_caption": ["A person trips across a rug."], "negative_caption": ["A person stretches across a rug."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_241", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/drooling_196.jpg", "positive_caption": ["A dog drools on the floor."], "negative_caption": ["A dog lands on the floor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_242", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_74.jpg", "positive_caption": ["A woman floats on water."], "negative_caption": ["A woman slips on water."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_243", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/embracing_52.jpg", "positive_caption": ["A girl embraces a young buck."], "negative_caption": ["A girl chases a young buck."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_245", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/eating_252.jpg", "positive_caption": ["A koala eats a leaf."], "negative_caption": ["A koala sucks a leaf."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_246", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/educating_7.jpg", "positive_caption": ["A woman educates a male child."], "negative_caption": ["A woman rams a male child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_247", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/restraining_73.jpg", "positive_caption": ["The people restrain the feline."], "negative_caption": ["The people hunt the feline."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_248", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_50.jpg", "positive_caption": ["A person packages you a chocolate."], "negative_caption": ["A person slips you a chocolate."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_249", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/speaking_142.jpg", "positive_caption": ["A man speaks to a woman."], "negative_caption": ["A man smells to a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_251", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_36.jpg", "positive_caption": ["A bee emerges from a compartment."], "negative_caption": ["A bee erupts from a compartment."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_252", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/typing_77.jpg", "positive_caption": ["A man types on a laptop."], "negative_caption": ["A man chews on a laptop."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_254", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/counting_14.jpg", "positive_caption": ["A young buck counts the cash."], "negative_caption": ["A young buck reads the cash."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_255", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_188.jpg", "positive_caption": ["A man rows in a canal boat."], "negative_caption": ["A man floats in a canal boat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_256", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/caressing_51.jpg", "positive_caption": ["A man caresses a man."], "negative_caption": ["A man chases a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_257", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_86.jpg", "positive_caption": ["A man scolds a male child."], "negative_caption": ["A man baptizes a male child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_258", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_284.jpg", "positive_caption": ["A woman lectures people."], "negative_caption": ["A woman reads people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_259", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_104.jpg", "positive_caption": ["A woman trains a child."], "negative_caption": ["A woman sucks a child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_260", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/selling_270.jpg", "positive_caption": ["A person sells such a merchandise."], "negative_caption": ["A person displays such a merchandise."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_261", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/asking_52.jpg", "positive_caption": ["A policeman asks about the people."], "negative_caption": ["A policeman talks about the people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_262", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/preaching_14.jpg", "positive_caption": ["A curate preaches people."], "negative_caption": ["A curate reads people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_263", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/typing_180.jpg", "positive_caption": ["A man types with a keyboard."], "negative_caption": ["A man talks with a keyboard."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_264", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_84.jpg", "positive_caption": ["A man floats on water."], "negative_caption": ["A man stumbles on water."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_265", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arranging_287.jpg", "positive_caption": ["A woman arranges for a flower."], "negative_caption": ["A woman asks for a flower."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_266", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunching_235.jpg", "positive_caption": ["A businessman hunches over a laptop."], "negative_caption": ["A businessman stumbles over a laptop."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_267", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/poking_16.jpg", "positive_caption": ["A woman pokes at the fire."], "negative_caption": ["A woman stares at the fire."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_268", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_79.jpg", "positive_caption": ["A person drives a car."], "negative_caption": ["A person boards a car."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_269", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_177.jpg", "positive_caption": ["A professor lectures people."], "negative_caption": ["A professor reads people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_270", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_196.jpg", "positive_caption": ["A male child spears the fish."], "negative_caption": ["A male child bites the fish."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_271", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/braiding_184.jpg", "positive_caption": ["A woman braids her hair."], "negative_caption": ["A woman swings her hair."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_273", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sewing_61.jpg", "positive_caption": ["A person sews the burlap."], "negative_caption": ["A person burns the burlap."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_274", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_46.jpg", "positive_caption": ["A child bites my hand."], "negative_caption": ["A child tugs my hand."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_276", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slouching_69.jpg", "positive_caption": ["A man slouches in a chair."], "negative_caption": ["A man types in a chair."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_278", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_181.jpg", "positive_caption": ["A soldier aims a sniper rifle."], "negative_caption": ["A soldier pilots a sniper rifle."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_279", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_307.jpg", "positive_caption": ["A person presses in a picture."], "negative_caption": ["A person floats in a picture."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_280", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chiseling_195.jpg", "positive_caption": ["A man chisels a metallic element."], "negative_caption": ["A man burns a metallic element."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_281", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lifting_176.jpg", "positive_caption": ["A man lifts a hammer."], "negative_caption": ["A man fetches a hammer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_282", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kicking_269.jpg", "positive_caption": ["A male kicks a football."], "negative_caption": ["A male tackles a football."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_283", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_292.jpg", "positive_caption": ["A man presses the interface."], "negative_caption": ["A man confronts the interface."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_284", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/talking_281.jpg", "positive_caption": ["A woman talks to a woman."], "negative_caption": ["A woman clings to a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_285", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/competing_9.jpg", "positive_caption": ["A runner competes in a race."], "negative_caption": ["A runner aims in a race."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_286", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/floating_242.jpg", "positive_caption": ["A woman floats on the body of water."], "negative_caption": ["A woman lands on the body of water."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_287", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/twisting_101.jpg", "positive_caption": ["A man twists his beard."], "negative_caption": ["A man tugs his beard."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_289", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gardening_110.jpg", "positive_caption": ["A male child gardens a trowel."], "negative_caption": ["A male child burns a trowel."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_290", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/buttoning_155.jpg", "positive_caption": ["A man buttons up a dress shirt."], "negative_caption": ["A man tugs up a dress shirt."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_291", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_87.jpg", "positive_caption": ["A person drives a boat."], "negative_caption": ["A person boards a boat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_292", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/handcuffing_85.jpg", "positive_caption": ["A person handcuffs a man."], "negative_caption": ["A person hunts a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_295", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/handcuffing_61.jpg", "positive_caption": ["A man handcuffs a person."], "negative_caption": ["A man counts a person."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_296", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_44.jpg", "positive_caption": ["A professor lectures as a student."], "negative_caption": ["A professor counts as a student."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_297", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/molding_115.jpg", "positive_caption": ["A man molds the plastic."], "negative_caption": ["A man releases the plastic."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_298", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_248.jpg", "positive_caption": ["A man aims a submachine gun."], "negative_caption": ["A man hunts a submachine gun."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_299", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/circling_162.jpg", "positive_caption": ["A shark circles the fish."], "negative_caption": ["A shark bites the fish."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_300", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shouting_299.jpg", "positive_caption": ["A woman shouts after a man."], "negative_caption": ["A woman hunts after a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_301", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_32.jpg", "positive_caption": ["A man reassures a woman."], "negative_caption": ["A man admires a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_302", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_76.jpg", "positive_caption": ["A man pees on the wall."], "negative_caption": ["A man types on the wall."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_303", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_304.jpg", "positive_caption": ["A killer whale emerges from water."], "negative_caption": ["A killer whale launches from water."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_304", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/milking_193.jpg", "positive_caption": ["A child milks a goat."], "negative_caption": ["A child bites a goat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_305", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_104.jpg", "positive_caption": ["A man scolds a woman."], "negative_caption": ["A man admires a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_306", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/barbecuing_81.jpg", "positive_caption": ["A man barbecues the meat."], "negative_caption": ["A man sniffs the meat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_307", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/foraging_45.jpg", "positive_caption": ["A man forages for a plant."], "negative_caption": ["A man begs for a plant."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_308", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_36.jpg", "positive_caption": ["A man spears the fish."], "negative_caption": ["A man bites the fish."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_309", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/educating_66.jpg", "positive_caption": ["A woman educates a child."], "negative_caption": ["A woman sucks a child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_311", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/asking_49.jpg", "positive_caption": ["A woman asks for a girl."], "negative_caption": ["A woman shops for a girl."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_312", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_245.jpg", "positive_caption": ["A woman instructs people."], "negative_caption": ["A woman hunts people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_313", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nuzzling_117.jpg", "positive_caption": ["A foal nuzzles the mare."], "negative_caption": ["A foal sucks the mare."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_317", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_145.jpg", "positive_caption": ["A man instructs people."], "negative_caption": ["A man hunts people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_318", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_178.jpg", "positive_caption": ["A man communicates with the people."], "negative_caption": ["A man hunts with the people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_319", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/typing_273.jpg", "positive_caption": ["A person types with a typewriter."], "negative_caption": ["A person talks with a typewriter."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_320", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_12.jpg", "positive_caption": ["A horse stumbles on the soil."], "negative_caption": ["A horse spits on the soil."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_321", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_127.jpg", "positive_caption": ["A woman instructs a woman."], "negative_caption": ["A woman hunts a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_322", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/attacking_4.jpg", "positive_caption": ["A kitten attacks his foot."], "negative_caption": ["A kitten licks his foot."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_323", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_358.jpg", "positive_caption": ["A woman bites into her bread."], "negative_caption": ["A woman chews into her bread."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_324", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/rowing_83.jpg", "positive_caption": ["A person rows on a boat."], "negative_caption": ["A person floats on a boat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_325", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_13.jpg", "positive_caption": ["A woman aims a gun."], "negative_caption": ["A woman hunts a gun."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_326", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_72.jpg", "positive_caption": ["A man bites fish."], "negative_caption": ["A man talks fish."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_327", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_207.jpg", "positive_caption": ["A woman reads from a novel."], "negative_caption": ["A woman emerges from a novel."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_328", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/releasing_40.jpg", "positive_caption": ["A person releases a bird."], "negative_caption": ["A person embraces a bird."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_329", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shouting_249.jpg", "positive_caption": ["A man shouts after a woman."], "negative_caption": ["A man aims after a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_330", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stitching_146.jpg", "positive_caption": ["A woman stitches the scissors."], "negative_caption": ["A woman admires the scissors."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_331", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/winking_13.jpg", "positive_caption": ["A man winks at a woman."], "negative_caption": ["A man glares at a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_332", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calming_175.jpg", "positive_caption": ["A woman calms her dog."], "negative_caption": ["A woman licks her dog."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_333", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_205.jpg", "positive_caption": ["A man aims for a paintball gun."], "negative_caption": ["A man shops for a paintball gun."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_334", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/turning_124.jpg", "positive_caption": ["A man turns the knob."], "negative_caption": ["A man tugs the knob."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_336", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shopping_189.jpg", "positive_caption": ["A woman shops for food."], "negative_caption": ["A woman begs for food."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_338", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_0.jpg", "positive_caption": ["A dog pees at a table."], "negative_caption": ["A dog sniffs at a table."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_340", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/typing_43.jpg", "positive_caption": ["A man types on a keyboard."], "negative_caption": ["A man talks on a keyboard."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_341", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/imitating_145.jpg", "positive_caption": ["A child imitates such a woman."], "negative_caption": ["A child embraces such a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_342", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_303.jpg", "positive_caption": ["A child tugs a rope."], "negative_caption": ["A child skips a rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_343", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_154.jpg", "positive_caption": ["A person presses an application."], "negative_caption": ["A person types an application."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_344", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_223.jpg", "positive_caption": ["A person bites their fingernail."], "negative_caption": ["A person chews their fingernail."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_345", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_9.jpg", "positive_caption": ["A mosquito emerges from an exoskeleton."], "negative_caption": ["A mosquito sucks from an exoskeleton."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_346", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_44.jpg", "positive_caption": ["A woman commutes on a bicycle."], "negative_caption": ["A woman emerges on a bicycle."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_347", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/measuring_12.jpg", "positive_caption": ["A butcher measures the water."], "negative_caption": ["A butcher blocks the water."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_348", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spearing_149.jpg", "positive_caption": ["A scuba diver spears a shark."], "negative_caption": ["A scuba diver tackles a shark."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_349", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/writing_262.jpg", "positive_caption": ["A teacher writes on a board."], "negative_caption": ["A teacher rows on a board."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_350", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_163.jpg", "positive_caption": ["A man phones a telephone."], "negative_caption": ["A man presses a telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_351", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_168.jpg", "positive_caption": ["A young buck calls a cellular telephone."], "negative_caption": ["A young buck dials a cellular telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_352", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_214.jpg", "positive_caption": ["A man admires a woman."], "negative_caption": ["A man ignores a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_353", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_148.jpg", "positive_caption": ["A teacher instructs a girl."], "negative_caption": ["A teacher types a girl."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_354", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stretching_270.jpg", "positive_caption": ["A lion stretches its back."], "negative_caption": ["A lion arches its back."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_355", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sucking_95.jpg", "positive_caption": ["A man sucks his thumb."], "negative_caption": ["A man chews his thumb."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_356", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_203.jpg", "positive_caption": ["A farmer tills a tractor."], "negative_caption": ["A farmer pilots a tractor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_357", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plummeting_89.jpg", "positive_caption": ["A man plummets from an airplane."], "negative_caption": ["A man emerges from an airplane."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_360", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_232.jpg", "positive_caption": ["A man bites at my ear."], "negative_caption": ["A man shouts at my ear."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_362", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_103.jpg", "positive_caption": ["A dog sits on a floor."], "negative_caption": ["A dog spits on a floor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_363", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/confronting_163.jpg", "positive_caption": ["The police confront a mob."], "negative_caption": ["The police assembles a mob."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_364", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_187.jpg", "positive_caption": ["A businesswoman trains a customer."], "negative_caption": ["A businesswoman confronts a customer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_366", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/smelling_1.jpg", "positive_caption": ["A dog smells the plant."], "negative_caption": ["A dog burns the plant."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_367", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interviewing_5.jpg", "positive_caption": ["A man interviews people."], "negative_caption": ["A man ignores people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_368", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_55.jpg", "positive_caption": ["A teacher trains a ballet dancer."], "negative_caption": ["A teacher encourages a ballet dancer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_369", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_171.jpg", "positive_caption": ["A swimmer emerges from the pond."], "negative_caption": ["A swimmer stumbles from the pond."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_370", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sniffing_399.jpg", "positive_caption": ["A feline sniffs the flower."], "negative_caption": ["A feline releases the flower."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_371", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/whipping_99.jpg", "positive_caption": ["A man whips a woman."], "negative_caption": ["A man admires a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_373", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_56.jpg", "positive_caption": ["A man instructs a male child."], "negative_caption": ["A man baptizes a male child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_374", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_177.jpg", "positive_caption": ["A groundhog bites his ear."], "negative_caption": ["A groundhog claws his ear."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_376", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/selling_144.jpg", "positive_caption": ["A man sells his food."], "negative_caption": ["A man sniffs his food."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_377", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_72.jpg", "positive_caption": ["A dog urinates under a tree."], "negative_caption": ["A dog slips under a tree."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_378", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_19.jpg", "positive_caption": ["A butcher packages meat."], "negative_caption": ["A butcher shops meat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_379", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/mending_228.jpg", "positive_caption": ["A man mends an air conditioner."], "negative_caption": ["A man burns an air conditioner."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_380", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/releasing_58.jpg", "positive_caption": ["A woman releases a bird."], "negative_caption": ["A woman pilots a bird."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_381", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_9.jpg", "positive_caption": ["A woman calls a cellular telephone."], "negative_caption": ["A woman dials a cellular telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_382", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ignoring_123.jpg", "positive_caption": ["A woman ignores a man."], "negative_caption": ["A woman admires a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_383", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_120.jpg", "positive_caption": ["A woman skips a jump rope."], "negative_caption": ["A woman releases a jump rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_384", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_147.jpg", "positive_caption": ["A man trains a woman."], "negative_caption": ["A man admires a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_386", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/guarding_277.jpg", "positive_caption": ["A dog guards a house."], "negative_caption": ["A dog decors a house."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_387", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_6.jpg", "positive_caption": ["A man slips to the floor."], "negative_caption": ["A man floats to the floor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_388", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/camping_18.jpg", "positive_caption": ["A man camps in a tent."], "negative_caption": ["A man hunches in a tent."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_389", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_271.jpg", "positive_caption": ["A dog pees over the grass."], "negative_caption": ["A dog stumbles over the grass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_390", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/licking_285.jpg", "positive_caption": ["A dog licks my neck."], "negative_caption": ["A dog sniffs my neck."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_391", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tying_222.jpg", "positive_caption": ["A child ties up a rope."], "negative_caption": ["A child trips up a rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_392", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_63.jpg", "positive_caption": ["A killer whale emerges from the body of water."], "negative_caption": ["A killer whale erupts from the body of water."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_393", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_231.jpg", "positive_caption": ["A wolf hunts the deer."], "negative_caption": ["A wolf confronts the deer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_394", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_23.jpg", "positive_caption": ["A cheetah hunts a deer."], "negative_caption": ["A cheetah claws a deer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_395", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/wrinkling_186.jpg", "positive_caption": ["An old woman wrinkles her brow."], "negative_caption": ["An old woman ducks her brow."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_396", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pressing_289.jpg", "positive_caption": ["A person presses a computer."], "negative_caption": ["A person boards a computer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_397", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_82.jpg", "positive_caption": ["A woman instructs a passenger."], "negative_caption": ["A woman boards a passenger."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_398", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_295.jpg", "positive_caption": ["A shark bites like a shark."], "negative_caption": ["A shark shells like a shark."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_399", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stretching_176.jpg", "positive_caption": ["A woman stretches her leg."], "negative_caption": ["A woman presses her leg."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_400", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_93.jpg", "positive_caption": ["An old man tills up a cultivator."], "negative_caption": ["An old man burns up a cultivator."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_401", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_60.jpg", "positive_caption": ["A man leads the sheep."], "negative_caption": ["A man releases the sheep."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_402", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/panhandling_89.jpg", "positive_caption": ["A man panhandles people."], "negative_caption": ["A man admires people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_403", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_308.jpg", "positive_caption": ["A man pees over a tree."], "negative_caption": ["A man hunches over a tree."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_404", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/riding_69.jpg", "positive_caption": ["A man rides the statue."], "negative_caption": ["A man admires the statue."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_405", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_116.jpg", "positive_caption": ["A woman skips down a jump rope."], "negative_caption": ["A woman slips down a jump rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_406", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bulldozing_91.jpg", "positive_caption": ["A man bulldozes the soil."], "negative_caption": ["A man tills the soil."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_408", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plummeting_33.jpg", "positive_caption": ["A man plummets from a helicopter."], "negative_caption": ["A man emerges from a helicopter."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_409", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_234.jpg", "positive_caption": ["A cat pees over a Kitty Litter."], "negative_caption": ["A cat hunches over a Kitty Litter."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_410", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_198.jpg", "positive_caption": ["A man coaches a male child."], "negative_caption": ["A man baptizes a male child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_411", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_0.jpg", "positive_caption": ["A buck chases after the deer."], "negative_caption": ["A buck emerges after the deer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_412", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_157.jpg", "positive_caption": ["An old man coaches people."], "negative_caption": ["An old man bothers people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_413", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_101.jpg", "positive_caption": ["A soldier leads a troop."], "negative_caption": ["A soldier trains a troop."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_414", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_215.jpg", "positive_caption": ["A man coaches a woman."], "negative_caption": ["A man admires a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_415", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/guarding_205.jpg", "positive_caption": ["A watchman guards a parking lot."], "negative_caption": ["A watchman boards a parking lot."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_416", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_195.jpg", "positive_caption": ["A policeman arrests a man."], "negative_caption": ["A policeman confronts a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_418", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_198.jpg", "positive_caption": ["A man bites his nail."], "negative_caption": ["A man tugs his nail."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_419", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_361.jpg", "positive_caption": ["A male child admires an old man."], "negative_caption": ["A male child confronts an old man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_420", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/mopping_21.jpg", "positive_caption": ["A woman mops on the floor."], "negative_caption": ["A woman slips on the floor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_421", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_296.jpg", "positive_caption": ["A woman phones a telephone."], "negative_caption": ["A woman dials a telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_422", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_180.jpg", "positive_caption": ["A man pees over a wall."], "negative_caption": ["A man stumbles over a wall."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_423", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_84.jpg", "positive_caption": ["A child urinates under a tree."], "negative_caption": ["A child ducks under a tree."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_424", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/imitating_118.jpg", "positive_caption": ["A male child imitates a male child."], "negative_caption": ["A male child trains a male child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_426", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/guarding_92.jpg", "positive_caption": ["A dog guards a tent."], "negative_caption": ["A dog flaps a tent."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_427", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_186.jpg", "positive_caption": ["A person tills up a tractor."], "negative_caption": ["A person trips up a tractor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_429", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plowing_157.jpg", "positive_caption": ["A man plows over a cow."], "negative_caption": ["A man stumbles over a cow."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_432", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/confronting_156.jpg", "positive_caption": ["The police confront a criminal."], "negative_caption": ["The police arrests a criminal."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_433", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/commuting_124.jpg", "positive_caption": ["A man commutes on a bicycle."], "negative_caption": ["A man emerges on a bicycle."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_434", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_203.jpg", "positive_caption": ["A man instructs his people."], "negative_caption": ["A man reassures his people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_435", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_235.jpg", "positive_caption": ["A man browses a book."], "negative_caption": ["A man types a book."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_437", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baking_62.jpg", "positive_caption": ["A woman bakes me a cake."], "negative_caption": ["A woman slips me a cake."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_440", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/training_223.jpg", "positive_caption": ["A businesswoman trains a colleague."], "negative_caption": ["A businesswoman interviews a colleague."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_441", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_21.jpg", "positive_caption": ["A woman works at work."], "negative_caption": ["A woman shouts at work."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_442", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punting_141.jpg", "positive_caption": ["A young buck punts a football."], "negative_caption": ["A young buck tackles a football."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_443", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_73.jpg", "positive_caption": ["A man complains to a woman."], "negative_caption": ["A man clings to a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_444", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/adjusting_286.jpg", "positive_caption": ["A person adjusts the module."], "negative_caption": ["A person inserts the module."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_445", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_98.jpg", "positive_caption": ["A conductor leads a marching band."], "negative_caption": ["A conductor coaches a marching band."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_446", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneading_128.jpg", "positive_caption": ["A chef kneads the dough."], "negative_caption": ["A chef types the dough."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_447", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_160.jpg", "positive_caption": ["A man calls on telephone."], "negative_caption": ["A man types on telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_448", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/miming_141.jpg", "positive_caption": ["A mime mimes happiness."], "negative_caption": ["A mime encourages happiness."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_449", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_283.jpg", "positive_caption": ["A man phones a cellular telephone."], "negative_caption": ["A man dials a cellular telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_450", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_198.jpg", "positive_caption": ["A man instructs a man."], "negative_caption": ["A man confronts a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_451", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_100.jpg", "positive_caption": ["A woman disembarks an airplane."], "negative_caption": ["A woman floats an airplane."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_452", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_30.jpg", "positive_caption": ["A policeman frisks the work force."], "negative_caption": ["A policeman exercises the work force."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_453", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_189.jpg", "positive_caption": ["A young buck packages up a broom."], "negative_caption": ["A young buck heaves up a broom."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_454", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_93.jpg", "positive_caption": ["A woman phones the telephone."], "negative_caption": ["A woman presses the telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_455", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ducking_68.jpg", "positive_caption": ["A man ducks behind a door."], "negative_caption": ["A man stumbles behind a door."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_456", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_345.jpg", "positive_caption": ["A woman tugs a rope."], "negative_caption": ["A woman skips a rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_457", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_288.jpg", "positive_caption": ["A woman communicates with a man."], "negative_caption": ["A woman competes with a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_458", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_82.jpg", "positive_caption": ["A man works the building."], "negative_caption": ["A man confronts the building."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_459", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_143.jpg", "positive_caption": ["The people skip the rope."], "negative_caption": ["The people trip the rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_461", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shushing_24.jpg", "positive_caption": ["A man shushes people."], "negative_caption": ["A man trains people."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_462", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flapping_183.jpg", "positive_caption": ["A bird flaps its wing."], "negative_caption": ["A bird flexes its wing."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_465", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/helping_267.jpg", "positive_caption": ["A man helps a man."], "negative_caption": ["A man confronts a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_466", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_220.jpg", "positive_caption": ["The police arrest a male."], "negative_caption": ["The police detains a male."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_467", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_281.jpg", "positive_caption": ["A man emerges from a swimming pool."], "negative_caption": ["A man stumbles from a swimming pool."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_468", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_192.jpg", "positive_caption": ["A man burns the cruiser."], "negative_caption": ["A man ducks the cruiser."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_469", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_37.jpg", "positive_caption": ["A man disembarks an airplane."], "negative_caption": ["A man confronts an airplane."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_470", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tilling_207.jpg", "positive_caption": ["A man tills up a tractor."], "negative_caption": ["A man heaves up a tractor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_471", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_238.jpg", "positive_caption": ["A dog hunts a rabbit."], "negative_caption": ["A dog claws a rabbit."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_472", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_115.jpg", "positive_caption": ["A man skips a jump rope."], "negative_caption": ["A man tows a jump rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_473", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/confronting_162.jpg", "positive_caption": ["A demonstrator confronts the police."], "negative_caption": ["A demonstrator phones the police."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_474", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pushing_75.jpg", "positive_caption": ["A woman pushes against a boulder."], "negative_caption": ["A woman stumbles against a boulder."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_476", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/calling_82.jpg", "positive_caption": ["A man calls the telephone."], "negative_caption": ["A man presses the telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_477", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reassuring_15.jpg", "positive_caption": ["A radiologist reassures a patient."], "negative_caption": ["A radiologist interviews a patient."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_478", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_204.jpg", "positive_caption": ["A woman skips the grass."], "negative_caption": ["A woman braids the grass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_479", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_92.jpg", "positive_caption": ["A soldier boards a ship."], "negative_caption": ["A soldier rows a ship."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_480", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/overflowing_231.jpg", "positive_caption": ["A seed overflows from the cup."], "negative_caption": ["A seed recovers from the cup."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_481", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/packaging_141.jpg", "positive_caption": ["A woman packages paperwork."], "negative_caption": ["A woman types paperwork."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_482", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/disembarking_84.jpg", "positive_caption": ["A girl disembarks an airplane."], "negative_caption": ["A girl tows an airplane."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_483", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_34.jpg", "positive_caption": ["The police arrest a woman."], "negative_caption": ["The police interviews a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_484", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interviewing_240.jpg", "positive_caption": ["A woman interviews a man."], "negative_caption": ["A woman trains a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_485", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/assembling_378.jpg", "positive_caption": ["A man assembles a bicycle."], "negative_caption": ["A man pedals a bicycle."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_486", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_54.jpg", "positive_caption": ["A mother scolds her son."], "negative_caption": ["A mother encourages her son."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_487", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_190.jpg", "positive_caption": ["A man aims a bow and arrow."], "negative_caption": ["A man spears a bow and arrow."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_488", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interviewing_212.jpg", "positive_caption": ["A woman interviews a woman."], "negative_caption": ["A woman trains a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_489", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/carrying_382.jpg", "positive_caption": ["A man carries a backpack."], "negative_caption": ["A man restrains a backpack."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_490", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_122.jpg", "positive_caption": ["A woman instructs a young person."], "negative_caption": ["A woman giggles a young person."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_491", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/paying_77.jpg", "positive_caption": ["A man pays for a cashier."], "negative_caption": ["A man shops for a cashier."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_492", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/mending_70.jpg", "positive_caption": ["A man mends the fabric."], "negative_caption": ["A man tugs the fabric."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_493", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/licking_128.jpg", "positive_caption": ["A lion licks a cub."], "negative_caption": ["A lion claws a cub."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_495", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tripping_218.jpg", "positive_caption": ["A man trips on his foot."], "negative_caption": ["A man spits on his foot."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_497", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/heaving_13.jpg", "positive_caption": ["A man heaves a tire."], "negative_caption": ["A man flaps a tire."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_498", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plowing_290.jpg", "positive_caption": ["A man plows a horse."], "negative_caption": ["A man trains a horse."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_499", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_82.jpg", "positive_caption": ["A helicopter lands on the ground."], "negative_caption": ["A helicopter flaps on the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_501", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/drooling_81.jpg", "positive_caption": ["A dog drools on the grass."], "negative_caption": ["A dog stumbles on the grass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_502", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/talking_77.jpg", "positive_caption": ["A woman talks to a man."], "negative_caption": ["A woman clings to a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_503", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_57.jpg", "positive_caption": ["A woman complains to another woman."], "negative_caption": ["A woman clings to another woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_504", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/embracing_223.jpg", "positive_caption": ["A woman embraces her daughter."], "negative_caption": ["A woman reassures her daughter."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_505", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interrogating_177.jpg", "positive_caption": ["A man interrogates a woman."], "negative_caption": ["A man trains a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_506", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pushing_326.jpg", "positive_caption": ["A man pushes a jeep."], "negative_caption": ["A man tows a jeep."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_507", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_101.jpg", "positive_caption": ["The police arrest a demonstrator."], "negative_caption": ["The police interviews a demonstrator."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_508", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/phoning_13.jpg", "positive_caption": ["A woman phones a cellular telephone."], "negative_caption": ["A woman aims a cellular telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_509", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ignoring_131.jpg", "positive_caption": ["A woman ignores a female child."], "negative_caption": ["A woman trains a female child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_510", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_51.jpg", "positive_caption": ["A woman reads from a textbook."], "negative_caption": ["A woman lecturs from a textbook."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_511", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_59.jpg", "positive_caption": ["A man unveils the award."], "negative_caption": ["A man tackles the award."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_512", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/asking_201.jpg", "positive_caption": ["A man asks for a woman."], "negative_caption": ["A man competes for a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_513", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/assembling_147.jpg", "positive_caption": ["A soldier assembles a bomb."], "negative_caption": ["A soldier aims a bomb."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_514", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/biting_394.jpg", "positive_caption": ["A dog bites my hand."], "negative_caption": ["A dog claws my hand."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_515", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/turning_109.jpg", "positive_caption": ["A woman turns on the doorknob."], "negative_caption": ["A woman tugs on the doorknob."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_517", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tripping_61.jpg", "positive_caption": ["A man trips on his leg."], "negative_caption": ["A man tugs on his leg."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_518", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/buttoning_83.jpg", "positive_caption": ["A woman buttons up a bridal gown."], "negative_caption": ["A woman tugs up a bridal gown."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_519", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bandaging_136.jpg", "positive_caption": ["A teacher bandages a girl."], "negative_caption": ["A teacher educates a girl."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_520", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/embracing_151.jpg", "positive_caption": ["A man embraces a woman."], "negative_caption": ["A man trains a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_521", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_158.jpg", "positive_caption": ["A woman complains to a man."], "negative_caption": ["A woman giggles to a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_522", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_90.jpg", "positive_caption": ["A man skips down a jump rope."], "negative_caption": ["A man trips down a jump rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_525", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_1.jpg", "positive_caption": ["A man complains to a waiter."], "negative_caption": ["A man whistles to a waiter."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_527", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/grilling_114.jpg", "positive_caption": ["A person grills up the food."], "negative_caption": ["A person packages up the food."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_528", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_10.jpg", "positive_caption": ["A ballplayer complains to an umpire."], "negative_caption": ["A ballplayer saluts to an umpire."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_529", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tackling_118.jpg", "positive_caption": ["A soccer player tackles the opposition."], "negative_caption": ["A soccer player coaches the opposition."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_530", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_77.jpg", "positive_caption": ["A man communicates with a woman."], "negative_caption": ["A man gambles with a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_531", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flapping_128.jpg", "positive_caption": ["A duck flaps its wing."], "negative_caption": ["A duck drums its wing."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_532", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/breaking_17.jpg", "positive_caption": ["A person breaks a window."], "negative_caption": ["A person bothers a window."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_535", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tugging_246.jpg", "positive_caption": ["A man tugs a rope."], "negative_caption": ["A man skips a rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_537", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stretching_309.jpg", "positive_caption": ["A coyote stretches its mouth."], "negative_caption": ["A coyote wrinkles its mouth."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_539", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_233.jpg", "positive_caption": ["An antelope chases a rabbit."], "negative_caption": ["An antelope ducks a rabbit."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_540", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/serving_76.jpg", "positive_caption": ["A bartender serves ale."], "negative_caption": ["A bartender brews ale."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_541", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/waving_113.jpg", "positive_caption": ["A mascot waves a flag."], "negative_caption": ["A mascot tackles a flag."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_542", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/competing_185.jpg", "positive_caption": ["A girl competes in gymnastics."], "negative_caption": ["A girl skips in gymnastics."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_543", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spitting_111.jpg", "positive_caption": ["A man spits his drink."], "negative_caption": ["A man laces his drink."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_544", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_263.jpg", "positive_caption": ["A man chases after a male child."], "negative_caption": ["A man claws after a male child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_545", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/tripping_125.jpg", "positive_caption": ["A man trips across a wire."], "negative_caption": ["A man claws across a wire."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_546", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interviewing_225.jpg", "positive_caption": ["A reporter interviews a policeman."], "negative_caption": ["A reporter arrests a policeman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_547", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_87.jpg", "positive_caption": ["A man works on a computer."], "negative_caption": ["A man buttons on a computer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_548", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_138.jpg", "positive_caption": ["An old man coaches a team."], "negative_caption": ["An old man skips a team."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_549", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_20.jpg", "positive_caption": ["A teacher instructs a woman."], "negative_caption": ["A teacher tackles a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_550", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/mopping_130.jpg", "positive_caption": ["A janitor mops the floor."], "negative_caption": ["A janitor tackles the floor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_551", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/unveiling_72.jpg", "positive_caption": ["A man unveils a painting."], "negative_caption": ["A man arranges a painting."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_552", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_150.jpg", "positive_caption": ["A woman sits in bed."], "negative_caption": ["A woman stumbles in bed."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_553", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skipping_162.jpg", "positive_caption": ["The people skip the jump rope."], "negative_caption": ["The people trip the jump rope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_554", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bulldozing_191.jpg", "positive_caption": ["A bulldozer bulldozes the soil."], "negative_caption": ["A bulldozer tills the soil."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_555", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_21.jpg", "positive_caption": ["A man chases after a woman."], "negative_caption": ["A man claws after a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_556", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/distracting_19.jpg", "positive_caption": ["A cellular telephone distracts the woman."], "negative_caption": ["A cellular telephone phones the woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_558", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/grilling_84.jpg", "positive_caption": ["A person grills the meat."], "negative_caption": ["A person bakes the meat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_559", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sniffing_3.jpg", "positive_caption": ["A man sniffs cocaine."], "negative_caption": ["A man bakes cocaine."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_561", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_33.jpg", "positive_caption": ["A horse stumbles on the grass."], "negative_caption": ["A horse skips on the grass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_562", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/skating_186.jpg", "positive_caption": ["A woman skates on an ice skate."], "negative_caption": ["A woman stumbles on an ice skate."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_563", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/handcuffing_0.jpg", "positive_caption": ["A man handcuffs a woman."], "negative_caption": ["A man baptizes a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_564", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/releasing_100.jpg", "positive_caption": ["A man releases a bird."], "negative_caption": ["A man calms a bird."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_565", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/admiring_2.jpg", "positive_caption": ["A woman admires such a man."], "negative_caption": ["A woman encourages such a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_567", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/dialing_192.jpg", "positive_caption": ["A woman dials a telephone."], "negative_caption": ["A woman phones a telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_571", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_213.jpg", "positive_caption": ["A father scolds his child."], "negative_caption": ["A father encourages his child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_572", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_39.jpg", "positive_caption": ["A ballplayer stumbles onto the ball field."], "negative_caption": ["A ballplayer rows onto the ball field."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_574", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/bandaging_18.jpg", "positive_caption": ["A doctor bandages a woman."], "negative_caption": ["A doctor educates a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_575", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_133.jpg", "positive_caption": ["A man aims for a cellular telephone."], "negative_caption": ["A man stumbles for a cellular telephone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_576", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_272.jpg", "positive_caption": ["A busman drives the school bus."], "negative_caption": ["A busman trips the school bus."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_577", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/handcuffing_71.jpg", "positive_caption": ["A woman handcuffs a man."], "negative_caption": ["A woman encourages a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_578", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/distracting_230.jpg", "positive_caption": ["A cellular telephone distracts the man."], "negative_caption": ["A cellular telephone bothers the man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_579", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/coaching_58.jpg", "positive_caption": ["A man coaches a child."], "negative_caption": ["A man arrests a child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_580", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_274.jpg", "positive_caption": ["A man hunts a bird."], "negative_caption": ["A man calms a bird."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_581", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/parachuting_19.jpg", "positive_caption": ["A man parachutes from a parachute."], "negative_caption": ["A man recovers from a parachute."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_582", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_23.jpg", "positive_caption": ["A man pees the door."], "negative_caption": ["A man trips the door."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_583", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_205.jpg", "positive_caption": ["A man instructs a colleague."], "negative_caption": ["A man bothers a colleague."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_584", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/dropping_247.jpg", "positive_caption": ["A paratrooper drops a parachute."], "negative_caption": ["A paratrooper parachutes a parachute."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_585", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interrogating_110.jpg", "positive_caption": ["A soldier interrogates a man."], "negative_caption": ["A soldier arrests a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_586", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spitting_124.jpg", "positive_caption": ["A man spits out his beverage."], "negative_caption": ["A man heaves out his beverage."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_587", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/helping_91.jpg", "positive_caption": ["A man helps a female child."], "negative_caption": ["A man arrests a female child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_589", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/brewing_85.jpg", "positive_caption": ["A man brews his coffee."], "negative_caption": ["A man laces his coffee."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_590", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shoveling_247.jpg", "positive_caption": ["A man shovels snow."], "negative_caption": ["A man tills snow."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_591", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plowing_158.jpg", "positive_caption": ["A farmer plows over a tractor."], "negative_caption": ["A farmer trips over a tractor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_592", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_199.jpg", "positive_caption": ["A hunter hunts a bird."], "negative_caption": ["A hunter claws a bird."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_593", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sowing_137.jpg", "positive_caption": ["A man sows a bucket."], "negative_caption": ["A man trips a bucket."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_594", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/cramming_152.jpg", "positive_caption": ["A male child crams up ice cream."], "negative_caption": ["A male child packages up ice cream."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_595", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_334.jpg", "positive_caption": ["A man sits in a chair."], "negative_caption": ["A man glares in a chair."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_596", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_44.jpg", "positive_caption": ["A woman stumbles onto the ground."], "negative_caption": ["A woman parachutes onto the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_597", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_352.jpg", "positive_caption": ["A toddler chases after a cat."], "negative_caption": ["A toddler paws after a cat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_598", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_34.jpg", "positive_caption": ["A mother scolds her daughter."], "negative_caption": ["A mother encourages her daughter."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_600", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/saluting_231.jpg", "positive_caption": ["A child salutes a soldier."], "negative_caption": ["A child camps a soldier."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_601", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chewing_341.jpg", "positive_caption": ["A dog chews a bone."], "negative_caption": ["A dog tows a bone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_602", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_63.jpg", "positive_caption": ["A woman kneels on the mat."], "negative_caption": ["A woman stumbles on the mat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_604", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baptizing_90.jpg", "positive_caption": ["A priest baptizes a baby."], "negative_caption": ["A priest lecturs a baby."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_605", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_190.jpg", "positive_caption": ["A truck tows a motorcycle."], "negative_caption": ["A truck taxis a motorcycle."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_607", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/deflecting_97.jpg", "positive_caption": ["A combatant deflects the blow."], "negative_caption": ["A combatant disciplines the blow."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_608", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/operating_154.jpg", "positive_caption": ["A man operates from a control panel."], "negative_caption": ["A man grimacs from a control panel."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_609", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/throwing_229.jpg", "positive_caption": ["A football player throws a football."], "negative_caption": ["A football player rows a football."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_610", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_189.jpg", "positive_caption": ["A man complains to a doctor."], "negative_caption": ["A man kneels to a doctor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_611", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_114.jpg", "positive_caption": ["A man boards a ship."], "negative_caption": ["A man rows a ship."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_612", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_45.jpg", "positive_caption": ["A husband scolds his wife."], "negative_caption": ["A husband phones his wife."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_613", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/selling_132.jpg", "positive_caption": ["A woman sells her food."], "negative_caption": ["A woman packages her food."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_614", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_65.jpg", "positive_caption": ["A woman communicates with a woman."], "negative_caption": ["A woman collides with a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_615", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/drumming_168.jpg", "positive_caption": ["A man drums a drum."], "negative_caption": ["A man claps a drum."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_616", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_260.jpg", "positive_caption": ["A baby urinates on a toilet."], "negative_caption": ["A baby kneels on a toilet."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_617", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_258.jpg", "positive_caption": ["A hunter chases after a American bison."], "negative_caption": ["A hunter forags after a American bison."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_618", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_38.jpg", "positive_caption": ["A woman scolds the girl."], "negative_caption": ["A woman distracts the girl."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_619", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_106.jpg", "positive_caption": ["A Transportation Security Administration frisks a man."], "negative_caption": ["A Transportation Security Administration detains a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_620", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sniffing_223.jpg", "positive_caption": ["A puppy sniffs the grass."], "negative_caption": ["A puppy tills the grass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_621", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interrogating_46.jpg", "positive_caption": ["A man interrogates a man."], "negative_caption": ["A man rots a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_624", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/falling_216.jpg", "positive_caption": ["A man falls down the stairs."], "negative_caption": ["A man skips down the stairs."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_625", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_99.jpg", "positive_caption": ["A man communicates with a child."], "negative_caption": ["A man camps with a child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_626", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_216.jpg", "positive_caption": ["A man pees in the toilet."], "negative_caption": ["A man kneels in the toilet."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_627", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_85.jpg", "positive_caption": ["A woman complains to an old woman."], "negative_caption": ["A woman preaches to an old woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_628", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/instructing_200.jpg", "positive_caption": ["A man instructs a drummer."], "negative_caption": ["A man claps a drummer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_629", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_217.jpg", "positive_caption": ["A duck sits in a nest."], "negative_caption": ["A duck forags in a nest."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_630", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_87.jpg", "positive_caption": ["A man communicates with another man."], "negative_caption": ["A man collides with another man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_631", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_39.jpg", "positive_caption": ["An airplane lands in a field."], "negative_caption": ["An airplane taxis in a field."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_633", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/milking_226.jpg", "positive_caption": ["A woman milks a cow."], "negative_caption": ["A woman rows a cow."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_634", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/complaining_31.jpg", "positive_caption": ["An old man complains to a doctor."], "negative_caption": ["An old man instructs to a doctor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_635", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_108.jpg", "positive_caption": ["A man pees at a toilet."], "negative_caption": ["A man kneels at a toilet."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_636", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_200.jpg", "positive_caption": ["A man browses the apparel."], "negative_caption": ["A man buttons the apparel."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_637", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_160.jpg", "positive_caption": ["A man kneels on the ground."], "negative_caption": ["A man rots on the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_638", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chewing_62.jpg", "positive_caption": ["A man chews a leaf."], "negative_caption": ["A man skips a leaf."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_639", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_233.jpg", "positive_caption": ["A woman browses the cheese."], "negative_caption": ["A woman milks the cheese."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_640", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_217.jpg", "positive_caption": ["An airplane lands on a lawn."], "negative_caption": ["An airplane taxis on a lawn."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_641", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/checking_288.jpg", "positive_caption": ["A man checks the label."], "negative_caption": ["A man tills the label."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_643", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/aiming_72.jpg", "positive_caption": ["A man aims for a rifle."], "negative_caption": ["A man kneels for a rifle."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_644", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chiseling_203.jpg", "positive_caption": ["A man chisels the limestone."], "negative_caption": ["A man unveils the limestone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_646", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/grilling_54.jpg", "positive_caption": ["A man grills a chicken."], "negative_caption": ["A man spears a chicken."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_647", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/guarding_83.jpg", "positive_caption": ["A policeman guards a statue."], "negative_caption": ["A policeman restrains a statue."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_648", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pedaling_260.jpg", "positive_caption": ["A woman pedals a bicycle."], "negative_caption": ["A woman rows a bicycle."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_649", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_265.jpg", "positive_caption": ["A lion hunts an animal."], "negative_caption": ["A lion spears an animal."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_650", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_128.jpg", "positive_caption": ["A woman chases after a male child."], "negative_caption": ["A woman milks after a male child."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_651", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_42.jpg", "positive_caption": ["A man sits on a sofa."], "negative_caption": ["A man kneels on a sofa."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_653", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_34.jpg", "positive_caption": ["A woman communicates with another woman."], "negative_caption": ["A woman camps with another woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_654", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/selling_77.jpg", "positive_caption": ["A woman sells soap."], "negative_caption": ["A woman brews soap."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_655", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_146.jpg", "positive_caption": ["A coastguardsman boards a helicopter."], "negative_caption": ["A coastguardsman tows a helicopter."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_656", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/plowing_35.jpg", "positive_caption": ["A man plows over a tractor."], "negative_caption": ["A man rows over a tractor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_657", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/nagging_145.jpg", "positive_caption": ["A woman nags a man."], "negative_caption": ["A woman gardens a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_658", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interviewing_202.jpg", "positive_caption": ["A reporter interviews a couple."], "negative_caption": ["A reporter tapes a couple."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_660", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_280.jpg", "positive_caption": ["A dog chases a dog."], "negative_caption": ["A dog boats a dog."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_662", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/emerging_10.jpg", "positive_caption": ["A woman emerges from the swimming pool."], "negative_caption": ["A woman complains from the swimming pool."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_663", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chewing_84.jpg", "positive_caption": ["A baseball coach chews his tobacco."], "negative_caption": ["A baseball coach coaches his tobacco."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_664", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/communicating_69.jpg", "positive_caption": ["A doctor communicates with an old woman."], "negative_caption": ["A doctor skates with an old woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_665", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_115.jpg", "positive_caption": ["A woman pees into a toilet."], "negative_caption": ["A woman kneels into a toilet."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_666", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_80.jpg", "positive_caption": ["A woman drives a tractor."], "negative_caption": ["A woman rows a tractor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_667", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_150.jpg", "positive_caption": ["A policeman arrests a Santa Claus."], "negative_caption": ["A policeman distracts a Santa Claus."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_668", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sucking_98.jpg", "positive_caption": ["A mosquito sucks at my skin."], "negative_caption": ["A mosquito stings at my skin."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_669", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_323.jpg", "positive_caption": ["A man sits against a wall."], "negative_caption": ["A man shelves against a wall."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_670", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/licking_291.jpg", "positive_caption": ["A cow licks its fur."], "negative_caption": ["A cow wrinkles its fur."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_671", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/confronting_171.jpg", "positive_caption": ["A man confronts a policeman."], "negative_caption": ["A man distracts a policeman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_672", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/reading_67.jpg", "positive_caption": ["A female reads the label."], "negative_caption": ["A female unveils the label."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_673", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/imitating_139.jpg", "positive_caption": ["A man imitates his father."], "negative_caption": ["A man reassures his father."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_674", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/working_76.jpg", "positive_caption": ["A man works with a desktop computer."], "negative_caption": ["A man communicates with a desktop computer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_675", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leaping_269.jpg", "positive_caption": ["A woman leaps from the ground."], "negative_caption": ["A woman complains from the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_676", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_32.jpg", "positive_caption": ["A man burns his rubbish."], "negative_caption": ["A man lecturs his rubbish."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_677", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interviewing_254.jpg", "positive_caption": ["A reporter interviews a man."], "negative_caption": ["A reporter lecturs a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_679", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/apprehending_92.jpg", "positive_caption": ["A person apprehends a watchman."], "negative_caption": ["A person complains a watchman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_680", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/shopping_215.jpg", "positive_caption": ["A woman shops at a grocery store."], "negative_caption": ["A woman winks at a grocery store."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_682", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/browsing_49.jpg", "positive_caption": ["A woman browses the apparel."], "negative_caption": ["A woman buttons the apparel."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_683", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_213.jpg", "positive_caption": ["A woman kneels on the floor."], "negative_caption": ["A woman rots on the floor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_684", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_38.jpg", "positive_caption": ["A man arrests a man."], "negative_caption": ["A man reassures a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_685", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/punching_155.jpg", "positive_caption": ["A man punches a punching bag."], "negative_caption": ["A man coaches a punching bag."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_686", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_23.jpg", "positive_caption": ["A man frisks a man."], "negative_caption": ["A man reassures a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_687", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/boarding_116.jpg", "positive_caption": ["A man boards an airplane."], "negative_caption": ["A man rows an airplane."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_688", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_77.jpg", "positive_caption": ["A hunter hunts a deer."], "negative_caption": ["A hunter camps a deer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_689", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/distracting_155.jpg", "positive_caption": ["A female child distracts a woman."], "negative_caption": ["A female child coaches a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_690", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/peeing_49.jpg", "positive_caption": ["A male child pees a toilet."], "negative_caption": ["A male child stitches a toilet."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_691", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_141.jpg", "positive_caption": ["A horse stumbles on the racetrack."], "negative_caption": ["A horse camps on the racetrack."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_692", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/distracting_75.jpg", "positive_caption": ["A doughnut distracts the man."], "negative_caption": ["A doughnut reassures the man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_693", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_215.jpg", "positive_caption": ["A man kneels on the floor."], "negative_caption": ["A man complains on the floor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_694", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kicking_37.jpg", "positive_caption": ["A young buck kicks a football."], "negative_caption": ["A young buck coaches a football."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_696", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_343.jpg", "positive_caption": ["A cheetah chases a bird."], "negative_caption": ["A cheetah barbecues a bird."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_697", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interrogating_56.jpg", "positive_caption": ["A detective interrogates a woman."], "negative_caption": ["A detective coaches a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_698", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_163.jpg", "positive_caption": ["A man burns his guitar."], "negative_caption": ["A man tapes his guitar."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_699", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_121.jpg", "positive_caption": ["A serviceman arrests a woman."], "negative_caption": ["A serviceman instructs a woman."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_700", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/lecturing_55.jpg", "positive_caption": ["A businesswoman lectures with a colleague."], "negative_caption": ["A businesswoman communicates with a colleague."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_701", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_227.jpg", "positive_caption": ["A child sits at a desk."], "negative_caption": ["A child kneels at a desk."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_702", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/scolding_20.jpg", "positive_caption": ["A boyfriend scolds his girlfriend."], "negative_caption": ["A boyfriend packages his girlfriend."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_703", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_243.jpg", "positive_caption": ["A lion chases after an antelope."], "negative_caption": ["A lion laces after an antelope."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_704", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/colliding_38.jpg", "positive_caption": ["A racer collides with the racer."], "negative_caption": ["A racer communicates with the racer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_705", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/leading_42.jpg", "positive_caption": ["A woman leads a parade."], "negative_caption": ["A woman preaches a parade."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_706", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/destroying_64.jpg", "positive_caption": ["A bear destroys a cooler."], "negative_caption": ["A bear inflates a cooler."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_707", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/flapping_18.jpg", "positive_caption": ["An eagle flaps its wing."], "negative_caption": ["An eagle wrinkles its wing."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_709", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/eating_336.jpg", "positive_caption": ["A male child eats a pizza."], "negative_caption": ["A male child packages a pizza."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_710", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/applauding_279.jpg", "positive_caption": ["A girl applauds the speaker."], "negative_caption": ["A girl distracts the speaker."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_711", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_52.jpg", "positive_caption": ["A man stumbles onto the ground."], "negative_caption": ["A man wades onto the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_712", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_42.jpg", "positive_caption": ["A man drives a car."], "negative_caption": ["A man pedals a car."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_713", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baptizing_73.jpg", "positive_caption": ["A curate baptizes a young buck."], "negative_caption": ["A curate distracts a young buck."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_714", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/juggling_131.jpg", "positive_caption": ["A ballplayer juggles a baseball."], "negative_caption": ["A ballplayer disciplines a baseball."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_716", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/panhandling_152.jpg", "positive_caption": ["A man panhandles a man."], "negative_caption": ["A man tills a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_717", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_47.jpg", "positive_caption": ["A dog urinates on the ground."], "negative_caption": ["A dog forags on the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_718", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/spitting_176.jpg", "positive_caption": ["A man spits out saliva."], "negative_caption": ["A man shovels out saliva."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_719", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/ignoring_97.jpg", "positive_caption": ["A girl ignores the man."], "negative_caption": ["A girl instructs the man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_721", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_204.jpg", "positive_caption": ["A car tows the trailer."], "negative_caption": ["A car fords the trailer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_722", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_251.jpg", "positive_caption": ["A man urinates against a wall."], "negative_caption": ["A man skates against a wall."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_723", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_63.jpg", "positive_caption": ["A policeman frisks a man."], "negative_caption": ["A policeman detains a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_724", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/sitting_197.jpg", "positive_caption": ["A woman sits on a sofa."], "negative_caption": ["A woman camps on a sofa."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_725", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/molding_6.jpg", "positive_caption": ["An artist molds the clay."], "negative_caption": ["An artist instructs the clay."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_727", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/knocking_11.jpg", "positive_caption": ["A man knocks the door."], "negative_caption": ["A man instructs the door."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_728", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/landing_131.jpg", "positive_caption": ["An airplane lands on a runway."], "negative_caption": ["An airplane instructs on a runway."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_729", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/arresting_233.jpg", "positive_caption": ["A policeman arrests an old man."], "negative_caption": ["A policeman subdues an old man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_730", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/confronting_199.jpg", "positive_caption": ["A policeman confronts a man."], "negative_caption": ["A policeman subdues a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_731", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pawing_209.jpg", "positive_caption": ["A dog paws the ground."], "negative_caption": ["A dog forags the ground."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_732", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/throwing_326.jpg", "positive_caption": ["A man throws a football."], "negative_caption": ["A man punts a football."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_733", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_291.jpg", "positive_caption": ["A man chases after a man."], "negative_caption": ["A man complains after a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_734", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/apprehending_195.jpg", "positive_caption": ["A traffic cop apprehends a man."], "negative_caption": ["A traffic cop instructs a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_735", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/licking_225.jpg", "positive_caption": ["A dog licks its nose."], "negative_caption": ["A dog wrinkles its nose."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_738", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_3.jpg", "positive_caption": ["A man stumbles to the floor."], "negative_caption": ["A man subdues to the floor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_739", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chasing_48.jpg", "positive_caption": ["A tiger chases a cow."], "negative_caption": ["A tiger subdues a cow."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_740", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_222.jpg", "positive_caption": ["A man burns the debris."], "negative_caption": ["A man unveils the debris."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_741", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/igniting_258.jpg", "positive_caption": ["A man ignites a cigarette."], "negative_caption": ["A man wrinkles a cigarette."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_742", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/baking_113.jpg", "positive_caption": ["An old man bakes his bread."], "negative_caption": ["An old man wrinkles his bread."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_743", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_136.jpg", "positive_caption": ["A dog urinates in the grass."], "negative_caption": ["A dog skates in the grass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_744", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/chiseling_87.jpg", "positive_caption": ["An old woman chisels the limestone."], "negative_caption": ["An old woman unveils the limestone."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_745", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_52.jpg", "positive_caption": ["A truck tows a trailer."], "negative_caption": ["A truck boats a trailer."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_746", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/slipping_140.jpg", "positive_caption": ["A man slips down the stairway."], "negative_caption": ["A man complains down the stairway."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_748", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_245.jpg", "positive_caption": ["A person burns the wood."], "negative_caption": ["A person instructs the wood."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_750", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/smashing_239.jpg", "positive_caption": ["A man smashes a window."], "negative_caption": ["A man instructs a window."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_751", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_113.jpg", "positive_caption": ["A truck tows a boat."], "negative_caption": ["A truck boats a boat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_752", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/erupting_76.jpg", "positive_caption": ["A vent erupts with smoke."], "negative_caption": ["A vent complains with smoke."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_753", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/subduing_50.jpg", "positive_caption": ["A policeman subdues an intruder."], "negative_caption": ["A policeman complains an intruder."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_754", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_60.jpg", "positive_caption": ["A truck tows a tractor."], "negative_caption": ["A truck fords a tractor."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_755", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pouncing_185.jpg", "positive_caption": ["A cheetah pounces prey."], "negative_caption": ["A cheetah wades prey."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_756", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_175.jpg", "positive_caption": ["A man stumbles into the stairs."], "negative_caption": ["A man complains into the stairs."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_759", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_176.jpg", "positive_caption": ["A truck tows a car."], "negative_caption": ["A truck fords a car."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_760", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/hunting_34.jpg", "positive_caption": ["A leopard hunts a crocodile."], "negative_caption": ["A leopard imitates a crocodile."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_761", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/kneeling_250.jpg", "positive_caption": ["A man kneels in the grass."], "negative_caption": ["A man pees in the grass."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_762", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/videotaping_45.jpg", "positive_caption": ["A man videotapes the fencing."], "negative_caption": ["A man unveils the fencing."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_763", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/subduing_150.jpg", "positive_caption": ["A policeman subdues a man."], "negative_caption": ["A policeman interrogs a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_764", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/interrogating_167.jpg", "positive_caption": ["An agent interrogates a man."], "negative_caption": ["An agent communicates a man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_765", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/erupting_123.jpg", "positive_caption": ["A vent erupts lava."], "negative_caption": ["A vent communicates lava."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_766", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_182.jpg", "positive_caption": ["A man urinates on a toilet."], "negative_caption": ["A man complains on a toilet."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_768", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/imitating_87.jpg", "positive_caption": ["A woman imitates the statue."], "negative_caption": ["A woman unveils the statue."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_769", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/towing_195.jpg", "positive_caption": ["A minivan tows a jet."], "negative_caption": ["A minivan imitates a jet."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_770", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/urinating_195.jpg", "positive_caption": ["A man urinates against a fence."], "negative_caption": ["A man molds against a fence."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_771", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/driving_85.jpg", "positive_caption": ["A woman drives a car."], "negative_caption": ["A woman pedals a car."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_772", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/frisking_162.jpg", "positive_caption": ["A police matron frisks the man."], "negative_caption": ["A police matron bandages the man."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_774", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/pulling_192.jpg", "positive_caption": ["A truck pulls a boat."], "negative_caption": ["A truck punts a boat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_775", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/stumbling_133.jpg", "positive_caption": ["A girl stumbles into the stairs."], "negative_caption": ["A girl molds into the stairs."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_776", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/burning_123.jpg", "positive_caption": ["A male burns rubbish."], "negative_caption": ["A male socials rubbish."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_777", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "swig/gnawing_178.jpg", "positive_caption": ["A man gnaws meat."], "negative_caption": ["A man grills meat."], "original_file_name": "action-replacement", "dataset": "SWiG", "key": "actions_test_778", "linguistic_phenomena": "actions", "original_split": "test"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000284024.jpg", "positive_caption": ["a woman sits on a bench holding a guitar in her lap. is this in a park? yes."], "negative_caption": ["a woman sits on a bench holding a guitar in her lap. is this in a park? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_0", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000440253.jpg", "positive_caption": ["5 people skiing in a snowy area surrounded by trees. is this a resort do you think? no."], "negative_caption": ["5 people skiing in a snowy area surrounded by trees. is this a resort do you think? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_1", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000097915.jpg", "positive_caption": ["a woman sitting at a table with a glass of wine while she is looking at her cellphone. is it a smartphone? yes."], "negative_caption": ["a woman sitting at a table with a glass of wine while she is looking at her cellphone. is it a smartphone? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_2", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000098602.jpg", "positive_caption": ["vegetables sit in bowls on a counter next to an orange. is it there with spoons? no."], "negative_caption": ["vegetables sit in bowls on a counter next to an orange. is it there with spoons? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_3", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000454168.jpg", "positive_caption": ["the surfer carries the surfboard on their head past the orange beach chairs. is this photo in color? yes."], "negative_caption": ["the surfer carries the surfboard on their head past the orange beach chairs. is this photo in color? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_5", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000174225.jpg", "positive_caption": ["an empty but clean public restroom with a toilet and automatic hand dryer. is this a single person bathroom? yes."], "negative_caption": ["an empty but clean public restroom with a toilet and automatic hand dryer. is this a single person bathroom? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_6", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000455297.jpg", "positive_caption": ["an old burgundy, black, and red steam locomotive on tracks near a wall and platform. is this a toy train set? no."], "negative_caption": ["an old burgundy, black, and red steam locomotive on tracks near a wall and platform. is this a toy train set? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_7", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000141126.jpg", "positive_caption": ["a man hitting a tennis ball with a racket. is he outside? yes."], "negative_caption": ["a man hitting a tennis ball with a racket. is he outside? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_8", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000295004.jpg", "positive_caption": ["2 men standing at different places on a flight of stairs outside. is it in color? no."], "negative_caption": ["2 men standing at different places on a flight of stairs outside. is it in color? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_9", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000495362.jpg", "positive_caption": ["a dog and a cat that are playing together. is this in a house? no."], "negative_caption": ["a dog and a cat that are playing together. is this in a house? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_11", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000095221.jpg", "positive_caption": ["an older woman is sitting on the ground next to bundles of bananas at a market. does it look like the usa? no."], "negative_caption": ["an older woman is sitting on the ground next to bundles of bananas at a market. does it look like the usa? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_12", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000508600.jpg", "positive_caption": ["the buildings are tall and in the middle of the city. is it sunny? yes."], "negative_caption": ["the buildings are tall and in the middle of the city. is it sunny? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_16", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000059153.jpg", "positive_caption": ["a small, red train cart stands alone on train tracks. are there any people in this picture? no."], "negative_caption": ["a small, red train cart stands alone on train tracks. are there any people in this picture? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_17", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000552399.jpg", "positive_caption": ["a black train parked in the grass with another train behind it. is it carrying coal? no."], "negative_caption": ["a black train parked in the grass with another train behind it. is it carrying coal? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_19", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000083289.jpg", "positive_caption": ["a white polar bear swimming under the water. is this an adult bear? yes."], "negative_caption": ["a white polar bear swimming under the water. is this an adult bear? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_22", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000179535.jpg", "positive_caption": ["an assortment of different foods on a table. is this in a home? no."], "negative_caption": ["an assortment of different foods on a table. is this in a home? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_23", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000196905.jpg", "positive_caption": ["2 people are riding on horses along a beach. are there any other people other than those on the 2 horses? yes."], "negative_caption": ["2 people are riding on horses along a beach. are there any other people other than those on the 2 horses? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_24", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000505558.jpg", "positive_caption": ["a dad takes of picture of him and his 2 sons brushing their teeth. is this in a bathroom? yes."], "negative_caption": ["a dad takes of picture of him and his 2 sons brushing their teeth. is this in a bathroom? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_26", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000457675.jpg", "positive_caption": ["4 women on a beach 1 facing 3 others who are holding surfboards. do they wear sunglasses? no."], "negative_caption": ["4 women on a beach 1 facing 3 others who are holding surfboards. do they wear sunglasses? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_27", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000520026.jpg", "positive_caption": ["a single giraffe eating off a branch in a wooden pen. is it a full grown giraffe? yes."], "negative_caption": ["a single giraffe eating off a branch in a wooden pen. is it a full grown giraffe? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_29", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000096607.jpg", "positive_caption": ["a person holding a sandwich with sausage and egg. is it colored? yes."], "negative_caption": ["a person holding a sandwich with sausage and egg. is it colored? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_30", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000542075.jpg", "positive_caption": ["a panoramic view of the kitchen and living room. is this photo is color? yes."], "negative_caption": ["a panoramic view of the kitchen and living room. is this photo is color? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_32", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000006446.jpg", "positive_caption": ["a man and woman pose together on skis on a snowy, mountainous terrain. is it snowing? no."], "negative_caption": ["a man and woman pose together on skis on a snowy, mountainous terrain. is it snowing? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_35", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000273836.jpg", "positive_caption": ["there is an open pizza box with a beer in it and a slice missing out of it the pizza is white pizza with tomatoes on it. is it american cheese pizza? yes."], "negative_caption": ["there is an open pizza box with a beer in it and a slice missing out of it the pizza is white pizza with tomatoes on it. is it american cheese pizza? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_36", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000470589.jpg", "positive_caption": ["a boy with a balloon posing before a stop sign. is this outdoors? yes."], "negative_caption": ["a boy with a balloon posing before a stop sign. is this outdoors? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_40", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000031706.jpg", "positive_caption": ["a person brushing their dogs teeth with a red toothbrush. are they in the bathroom? no."], "negative_caption": ["a person brushing their dogs teeth with a red toothbrush. are they in the bathroom? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_41", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000565956.jpg", "positive_caption": ["a batter sitting at home plate on a major league baseball field. can you tell what major league team this is? no."], "negative_caption": ["a batter sitting at home plate on a major league baseball field. can you tell what major league team this is? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_42", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000220643.jpg", "positive_caption": ["a calico cat has its head on the keyboard of a laptop computer. does he have his eyes open? yes."], "negative_caption": ["a calico cat has its head on the keyboard of a laptop computer. does he have his eyes open? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_43", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000261004.jpg", "positive_caption": ["a woman is holding her phone over her head while standing on a beach. is the woman taking a photo with her phone? yes."], "negative_caption": ["a woman is holding her phone over her head while standing on a beach. is the woman taking a photo with her phone? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_44", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000552120.jpg", "positive_caption": ["a man playing tennis about to hit a ball. can you see his opponent? no."], "negative_caption": ["a man playing tennis about to hit a ball. can you see his opponent? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_45", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000154609.jpg", "positive_caption": ["a man is in the air while wearing a black and purple hat. is he doing some kind of sport? yes."], "negative_caption": ["a man is in the air while wearing a black and purple hat. is he doing some kind of sport? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_49", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000080703.jpg", "positive_caption": ["a man stands bent over in the ready position with a tennis racket between his legs. is this outside? yes."], "negative_caption": ["a man stands bent over in the ready position with a tennis racket between his legs. is this outside? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_50", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000172461.jpg", "positive_caption": ["a dog on a carpet looking at the legs of a person. is this picture in color? yes."], "negative_caption": ["a dog on a carpet looking at the legs of a person. is this picture in color? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_52", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000324850.jpg", "positive_caption": ["image of a red lobster restaurant from a street a one-way sign and street light is visible, and a man in an orange shirt is walking toward the entrance. is it daytime? yes."], "negative_caption": ["image of a red lobster restaurant from a street a one-way sign and street light is visible, and a man in an orange shirt is walking toward the entrance. is it daytime? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_54", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000549007.jpg", "positive_caption": ["a dump truck sitting in a parking lot. is this the only vehicle? no."], "negative_caption": ["a dump truck sitting in a parking lot. is this the only vehicle? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_56", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000406653.jpg", "positive_caption": ["5 planes doing acrobats in the sky leaving trails. is this an airshow? yes."], "negative_caption": ["5 planes doing acrobats in the sky leaving trails. is this an airshow? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_57", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000487201.jpg", "positive_caption": ["the front of 2 green and yellow dump trucks parked. is this downtown? no."], "negative_caption": ["the front of 2 green and yellow dump trucks parked. is this downtown? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_58", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000574545.jpg", "positive_caption": ["a red and white clock tower with latticework and the words taerofx market. is this outside? yes."], "negative_caption": ["a red and white clock tower with latticework and the words taerofx market. is this outside? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_59", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000488570.jpg", "positive_caption": ["a green bus on the street with a yellow bus in the background. is this a busy street? no."], "negative_caption": ["a green bus on the street with a yellow bus in the background. is this a busy street? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_61", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000073638.jpg", "positive_caption": ["2 zebras in the wild, in the grass with mountains in the background. is it during the day? yes."], "negative_caption": ["2 zebras in the wild, in the grass with mountains in the background. is it during the day? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_62", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000193521.jpg", "positive_caption": ["the man is talking on his cell phone whilst making a strange face as someone else in a ny beanie has a face of shock on a busy street corner. is it daytime? no."], "negative_caption": ["the man is talking on his cell phone whilst making a strange face as someone else in a ny beanie has a face of shock on a busy street corner. is it daytime? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_63", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000449230.jpg", "positive_caption": ["a man with a pair of scissors cuts some kind of wrap from another man's arm. is he a doctor? no."], "negative_caption": ["a man with a pair of scissors cuts some kind of wrap from another man's arm. is he a doctor? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_65", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000049132.jpg", "positive_caption": ["a car is behind a taxi at a red light. is this a color picture? yes."], "negative_caption": ["a car is behind a taxi at a red light. is this a color picture? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_66", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000078236.jpg", "positive_caption": ["a traffic light flashing in its yellow signal. is it in the city? no."], "negative_caption": ["a traffic light flashing in its yellow signal. is it in the city? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_67", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000146314.jpg", "positive_caption": ["4 asian women in light blue dresses are posing on a stage holding decorative umbrellas. is it raining? no."], "negative_caption": ["4 asian women in light blue dresses are posing on a stage holding decorative umbrellas. is it raining? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_69", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000122826.jpg", "positive_caption": ["several people visit a monument statue on a cold day. is it in washington? yes."], "negative_caption": ["several people visit a monument statue on a cold day. is it in washington? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_70", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000341783.jpg", "positive_caption": ["a young girl sitting on a dock playing on a cell phone. is it a smartphone? no."], "negative_caption": ["a young girl sitting on a dock playing on a cell phone. is it a smartphone? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_71", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000332604.jpg", "positive_caption": ["a street with several buildings and cars driving. does this look like a large city? no."], "negative_caption": ["a street with several buildings and cars driving. does this look like a large city? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_72", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000369874.jpg", "positive_caption": ["a white bed decorated with pink and yellow flowers. is this a bedroom? yes."], "negative_caption": ["a white bed decorated with pink and yellow flowers. is this a bedroom? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_76", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000424433.jpg", "positive_caption": ["many people wearing helmets and skiing down a snowy hill. is it snowing? yes."], "negative_caption": ["many people wearing helmets and skiing down a snowy hill. is it snowing? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_78", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000451072.jpg", "positive_caption": ["a group of giraffes walk next to a wooden fence. are they eating anything? no."], "negative_caption": ["a group of giraffes walk next to a wooden fence. are they eating anything? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_79", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000541928.jpg", "positive_caption": ["a small, very cramped, odd looking bathroom that is white. is it colored? yes."], "negative_caption": ["a small, very cramped, odd looking bathroom that is white. is it colored? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_80", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000332391.jpg", "positive_caption": ["someone is being detained by 2 people with 2 others looking in the background. is this in an airport? no."], "negative_caption": ["someone is being detained by 2 people with 2 others looking in the background. is this in an airport? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_81", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000577115.jpg", "positive_caption": ["a tiled, mosaic round pizza oven stands in the corner in front of a glass display case filled with metal bowls. is this photo in color? yes."], "negative_caption": ["a tiled, mosaic round pizza oven stands in the corner in front of a glass display case filled with metal bowls. is this photo in color? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_82", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000507735.jpg", "positive_caption": ["a man is painted silver paint and is posing on a beach. is he painting? no."], "negative_caption": ["a man is painted silver paint and is posing on a beach. is he painting? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_83", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000562944.jpg", "positive_caption": ["a black and white photo of a boy doing tricks with a skateboard. is this photo in color? no."], "negative_caption": ["a black and white photo of a boy doing tricks with a skateboard. is this photo in color? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_84", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000411239.jpg", "positive_caption": ["2 motorcycles and a pick up truck parked parallel to each other. is this in a showroom? no."], "negative_caption": ["2 motorcycles and a pick up truck parked parallel to each other. is this in a showroom? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_87", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000275692.jpg", "positive_caption": ["some deers standing in the middle of a road. is it colored? yes."], "negative_caption": ["some deers standing in the middle of a road. is it colored? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_88", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000098551.jpg", "positive_caption": ["a man is in a gym with a racquet in front of a woman with a racquet. is it a professional picture? no."], "negative_caption": ["a man is in a gym with a racquet in front of a woman with a racquet. is it a professional picture? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_89", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000553329.jpg", "positive_caption": ["a black bear is walking into a river. is this a big bear? yes."], "negative_caption": ["a black bear is walking into a river. is this a big bear? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_90", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000184249.jpg", "positive_caption": ["a man standing on a boardwalk holding a surfboard. is it in color? yes."], "negative_caption": ["a man standing on a boardwalk holding a surfboard. is it in color? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_91", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000572721.jpg", "positive_caption": ["3 or 4 giraffes are outside in a field with a shrub or tree. is this in a zoo? no."], "negative_caption": ["3 or 4 giraffes are outside in a field with a shrub or tree. is this in a zoo? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_93", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000510821.jpg", "positive_caption": ["gray boxes surrounding a fire hydrant with red knobs. is this outdoors? yes."], "negative_caption": ["gray boxes surrounding a fire hydrant with red knobs. is this outdoors? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_94", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000080912.jpg", "positive_caption": ["a man wearing a button down shirt and patterned tie smiles. is this photo in color? yes."], "negative_caption": ["a man wearing a button down shirt and patterned tie smiles. is this photo in color? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_96", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000087960.jpg", "positive_caption": ["a clean space with a mirror and a disco ball. is this a club? no."], "negative_caption": ["a clean space with a mirror and a disco ball. is this a club? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_97", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000212772.jpg", "positive_caption": ["a motorcycle parked on the side of a mountainous road. is this a black and white image? no."], "negative_caption": ["a motorcycle parked on the side of a mountainous road. is this a black and white image? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_99", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000045450.jpg", "positive_caption": ["the outside of a comedy club in the middle of a street. is it night? no."], "negative_caption": ["the outside of a comedy club in the middle of a street. is it night? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_101", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000385006.jpg", "positive_caption": ["a sink with it's faucet running and hand soap. is it a stainless steel sink? no."], "negative_caption": ["a sink with it's faucet running and hand soap. is it a stainless steel sink? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_105", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000107888.jpg", "positive_caption": ["a toilet with a lot of graffiti on the walls surrounding it. is it a public restroom? yes."], "negative_caption": ["a toilet with a lot of graffiti on the walls surrounding it. is it a public restroom? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_107", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000454628.jpg", "positive_caption": ["a cake stand with different desserts on it. is this indoors? yes."], "negative_caption": ["a cake stand with different desserts on it. is this indoors? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_109", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000057635.jpg", "positive_caption": ["a bathtub surround by small blue and white tiles. is this inside? yes."], "negative_caption": ["a bathtub surround by small blue and white tiles. is this inside? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_110", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000087445.jpg", "positive_caption": ["many people walking on the sidewalk and others sitting on the steps in a city scene. is it daytime? yes."], "negative_caption": ["many people walking on the sidewalk and others sitting on the steps in a city scene. is it daytime? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_114", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000220675.jpg", "positive_caption": ["numerous animals are grazing in a large field with grass and bushes. are they exotic animals? no."], "negative_caption": ["numerous animals are grazing in a large field with grass and bushes. are they exotic animals? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_115", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000369282.jpg", "positive_caption": ["a young boy peeling carrots into a plastic bag. is this a color photo? yes."], "negative_caption": ["a young boy peeling carrots into a plastic bag. is this a color photo? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_116", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000351712.jpg", "positive_caption": ["a tennis player extends her racket to hit the ball. is she wearing a skirt? yes."], "negative_caption": ["a tennis player extends her racket to hit the ball. is she wearing a skirt? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_118", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000143747.jpg", "positive_caption": ["white colored statues of men holding up clocks. is this inside? no."], "negative_caption": ["white colored statues of men holding up clocks. is this inside? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_119", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000116254.jpg", "positive_caption": ["a man wearing a vest walking a dog across the street. is it dark out? no."], "negative_caption": ["a man wearing a vest walking a dog across the street. is it dark out? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_120", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000293443.jpg", "positive_caption": ["2 people playing tennis olympic emblem on fence in purple girl in blue tennis outfit and girl with a red and blue tennis outfit 2 people standing against the wall. is this a competition? yes."], "negative_caption": ["2 people playing tennis olympic emblem on fence in purple girl in blue tennis outfit and girl with a red and blue tennis outfit 2 people standing against the wall. is this a competition? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_121", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000342578.jpg", "positive_caption": ["a sign for horse crossing is on a post in front of a sloping hill. is this a color picture? yes."], "negative_caption": ["a sign for horse crossing is on a post in front of a sloping hill. is this a color picture? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_126", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000355065.jpg", "positive_caption": ["a gray, red and yellow train stopped at the side of the track under a blue sky. is this a toy train? no."], "negative_caption": ["a gray, red and yellow train stopped at the side of the track under a blue sky. is this a toy train? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_127", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000578761.jpg", "positive_caption": ["2 identical buses are parked on a street, next to some apartment buildings. are they transportation city busses? yes."], "negative_caption": ["2 identical buses are parked on a street, next to some apartment buildings. are they transportation city busses? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_129", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000325630.jpg", "positive_caption": ["a bathroom with 2 sinks and a lot of towels. is it brightly lit? yes."], "negative_caption": ["a bathroom with 2 sinks and a lot of towels. is it brightly lit? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_130", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000465837.jpg", "positive_caption": ["a woman in a brown shirt is gasping. is she inside? yes."], "negative_caption": ["a woman in a brown shirt is gasping. is she inside? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_132", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000242109.jpg", "positive_caption": ["a young girl shows off her teddy bear through a train window. is this in color? no."], "negative_caption": ["a young girl shows off her teddy bear through a train window. is this in color? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_133", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000130808.jpg", "positive_caption": ["a man in a large body of water parasailing. is this at a beach? no."], "negative_caption": ["a man in a large body of water parasailing. is this at a beach? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_134", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000471071.jpg", "positive_caption": ["a group of skiers posed for a picture with a large resort at a distance in the background. is this a modern day photo? yes."], "negative_caption": ["a group of skiers posed for a picture with a large resort at a distance in the background. is this a modern day photo? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_135", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000249784.jpg", "positive_caption": ["the scene consists of multiple people standing on a rock patio, and they are surrounded by 3 benches, a garden maze, and buildings. is this a party? no."], "negative_caption": ["the scene consists of multiple people standing on a rock patio, and they are surrounded by 3 benches, a garden maze, and buildings. is this a party? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_136", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000093813.jpg", "positive_caption": ["a cat is laying on a sunny windowsill behind a cabinet. is this a color picture? yes."], "negative_caption": ["a cat is laying on a sunny windowsill behind a cabinet. is this a color picture? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_137", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000493142.jpg", "positive_caption": ["3 different colored and patterned ties on display. is this in a store? yes."], "negative_caption": ["3 different colored and patterned ties on display. is this in a store? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_139", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000459253.jpg", "positive_caption": ["a man and woman sitting at a table with 15 wine glasses. is this an older couple? no."], "negative_caption": ["a man and woman sitting at a table with 15 wine glasses. is this an older couple? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_141", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000385479.jpg", "positive_caption": ["a workman stands on a ladder to fix a traffic light. is this in a city? yes."], "negative_caption": ["a workman stands on a ladder to fix a traffic light. is this in a city? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_142", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000512753.jpg", "positive_caption": ["an outside market with large tables all filled with bananas and 1 man selling them. is it in color the pic? yes."], "negative_caption": ["an outside market with large tables all filled with bananas and 1 man selling them. is it in color the pic? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_146", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000376152.jpg", "positive_caption": ["a white computer mouse sitting on top of a mouse pad. is this in color? yes."], "negative_caption": ["a white computer mouse sitting on top of a mouse pad. is this in color? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_147", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000416080.jpg", "positive_caption": ["a barbed wire topped chain link fence with a sign and buildings in the background. is this a city scene? no."], "negative_caption": ["a barbed wire topped chain link fence with a sign and buildings in the background. is this a city scene? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_149", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000143389.jpg", "positive_caption": ["a man talking on a cell phone in a parking lot. is it daytime? yes."], "negative_caption": ["a man talking on a cell phone in a parking lot. is it daytime? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_150", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000017447.jpg", "positive_caption": ["a baseball player getting ready to bat during a baseball game. is he she a professional player? yes."], "negative_caption": ["a baseball player getting ready to bat during a baseball game. is he she a professional player? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_152", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000315349.jpg", "positive_caption": ["a yummy looking plate of beef and vegetable stir fry is ready to be eaten. is this indoors? yes."], "negative_caption": ["a yummy looking plate of beef and vegetable stir fry is ready to be eaten. is this indoors? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_154", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000084885.jpg", "positive_caption": ["a lone giraffe walking across a dirt road. is it in a zoo? no."], "negative_caption": ["a lone giraffe walking across a dirt road. is it in a zoo? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_155", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000033648.jpg", "positive_caption": ["a metal bed with a white blanket and map on the wall. is this a world map on the wall? yes."], "negative_caption": ["a metal bed with a white blanket and map on the wall. is this a world map on the wall? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_156", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000381618.jpg", "positive_caption": ["2 adult elephants playing with a younger elephant in a field. do they have tusks? no."], "negative_caption": ["2 adult elephants playing with a younger elephant in a field. do they have tusks? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_157", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000447518.jpg", "positive_caption": ["an elephant standing by some trees with a broken tusk. is it an adult elephant? yes."], "negative_caption": ["an elephant standing by some trees with a broken tusk. is it an adult elephant? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_158", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000464058.jpg", "positive_caption": ["an old man riding a wheelchair in the grass. is this in a park? no."], "negative_caption": ["an old man riding a wheelchair in the grass. is this in a park? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_159", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000321392.jpg", "positive_caption": ["a girl and boy sitting in the living room and playing a game. are they younger than 5? no."], "negative_caption": ["a girl and boy sitting in the living room and playing a game. are they younger than 5? yes."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_160", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/val/VisualDialog_val2018_000000366853.jpg", "positive_caption": ["2 zebras with their heads down are walking along a dirt road. are they walking away from the camera? yes."], "negative_caption": ["2 zebras with their heads down are walking along a dirt road. are they walking away from the camera? no."], "original_file_name": "coreference-hard", "dataset": "VisDial_v1.0", "key": "coref_test_161", "linguistic_phenomena": "coreference", "original_split": "val"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000254009.jpg", "positive_caption": ["a group of giraffe standing next to each other in a field. is this picture in color? yes."], "negative_caption": ["a group of giraffe standing next to each other in a field. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_528", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000358965.jpg", "positive_caption": ["several people can be seen out in the water. are there any animals in this photo? no."], "negative_caption": ["several people can be seen out in the water. are there any animals in this photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2055", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000410632.jpg", "positive_caption": ["back view of 3 men on a baseball field. is this color? yes."], "negative_caption": ["back view of 3 men on a baseball field. is this color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9439", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000390183.jpg", "positive_caption": ["2 cats play with each other near some computers. is this a color photo? yes."], "negative_caption": ["2 cats play with each other near some computers. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1729", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000450695.jpg", "positive_caption": ["a large long train on a steel track. is this picture in color? yes."], "negative_caption": ["a large long train on a steel track. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8575", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000536369.jpg", "positive_caption": ["an old fashioned stove with some pots on it. is it indoors? yes."], "negative_caption": ["an old fashioned stove with some pots on it. is it indoors? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9591", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000075254.jpg", "positive_caption": ["the giraffe is white with black spots on it's head. is this really a white and black giraffe? yes."], "negative_caption": ["the giraffe is white with black spots on it's head. is this really a white and black giraffe? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_552", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000499451.jpg", "positive_caption": ["a women sits on the grass with dogs all around. is the woman in her backyard? no."], "negative_caption": ["a women sits on the grass with dogs all around. is the woman in her backyard? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_529", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000133386.jpg", "positive_caption": ["an edited photo showing a single boy performing various skateboard tricks in a single picture. is it the same boy in all the images? yes."], "negative_caption": ["an edited photo showing a single boy performing various skateboard tricks in a single picture. is it the same boy in all the images? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_11061", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000030548.jpg", "positive_caption": ["a man with a beard in glasses grinning at the camera. is his beard long? no."], "negative_caption": ["a man with a beard in glasses grinning at the camera. is his beard long? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8470", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000130295.jpg", "positive_caption": ["a couple standing under an umbrella while looking at a bag. are they holding hands? no."], "negative_caption": ["a couple standing under an umbrella while looking at a bag. are they holding hands? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5923", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000035211.jpg", "positive_caption": ["a young child holding a racquet sits in a chair with a dog. is it indoor? no."], "negative_caption": ["a young child holding a racquet sits in a chair with a dog. is it indoor? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_55", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000414577.jpg", "positive_caption": ["a book that is on the edge of a desk. is this a color photo? yes."], "negative_caption": ["a book that is on the edge of a desk. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1457", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000153938.jpg", "positive_caption": ["a person sitting at a table with a pan of pizza. is this indoors? no."], "negative_caption": ["a person sitting at a table with a pan of pizza. is this indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1584", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000136941.jpg", "positive_caption": ["cows and calves milling on a dirt road. is this in color? yes."], "negative_caption": ["cows and calves milling on a dirt road. is this in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9387", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000307668.jpg", "positive_caption": ["there is a dog with his head out of the window. is this in color? no."], "negative_caption": ["there is a dog with his head out of the window. is this in color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10611", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000232279.jpg", "positive_caption": ["he is eating lunch with his mobile phone on the tray. is this indoors? yes."], "negative_caption": ["he is eating lunch with his mobile phone on the tray. is this indoors? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7128", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000467537.jpg", "positive_caption": ["a girl at work is reading in the kitchen. is this a color photo? yes."], "negative_caption": ["a girl at work is reading in the kitchen. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_292", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000128297.jpg", "positive_caption": ["a large picture of a man with a mustache and a bird on his shoulder. is man taking his own picture? no."], "negative_caption": ["a large picture of a man with a mustache and a bird on his shoulder. is man taking his own picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5209", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000562192.jpg", "positive_caption": ["a man skate boarding down a street near stores. is this a young man? yes."], "negative_caption": ["a man skate boarding down a street near stores. is this a young man? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3161", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000279616.jpg", "positive_caption": ["a train full of dead bodies and soldiers is moving down tracks. is it color image? no."], "negative_caption": ["a train full of dead bodies and soldiers is moving down tracks. is it color image? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5919", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000400379.jpg", "positive_caption": ["a man sits in front of a bowl of bananas and grapes. is he looking at the bowl? no."], "negative_caption": ["a man sits in front of a bowl of bananas and grapes. is he looking at the bowl? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2680", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000188824.jpg", "positive_caption": ["a cat sits on the armrest of a couch beside the remote control. is he asleep? no."], "negative_caption": ["a cat sits on the armrest of a couch beside the remote control. is he asleep? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10483", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000463944.jpg", "positive_caption": ["a living room with a tv and shelving. is it a big tv? no."], "negative_caption": ["a living room with a tv and shelving. is it a big tv? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3600", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000272269.jpg", "positive_caption": ["a cake is sitting on a silver tray on a table. is it a birthday cake? no."], "negative_caption": ["a cake is sitting on a silver tray on a table. is it a birthday cake? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3246", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000209722.jpg", "positive_caption": ["a man plowing a field with horses and sit-on plow. is this a color photo? no."], "negative_caption": ["a man plowing a field with horses and sit-on plow. is this a color photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1782", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000320905.jpg", "positive_caption": ["a giraffe inside of a wooden fence at a zoo. is the giraffe standing with it's head up? yes."], "negative_caption": ["a giraffe inside of a wooden fence at a zoo. is the giraffe standing with it's head up? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8081", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000366614.jpg", "positive_caption": ["a little girl wearing pink and gray standing on skis in the snow. is she a kid? yes."], "negative_caption": ["a little girl wearing pink and gray standing on skis in the snow. is she a kid? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_20", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000367630.jpg", "positive_caption": ["the women are both laying down 1 is reading. is this indoors? yes."], "negative_caption": ["the women are both laying down 1 is reading. is this indoors? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_160", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000447208.jpg", "positive_caption": ["a man making hand gestures over a highly decorated cake. is this photo in color? yes."], "negative_caption": ["a man making hand gestures over a highly decorated cake. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7615", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000203876.jpg", "positive_caption": ["a person sitting down eating something next to a window. is this photo black and white? no."], "negative_caption": ["a person sitting down eating something next to a window. is this photo black and white? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5877", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000356421.jpg", "positive_caption": ["a person is performing a trick on a skateboard. is this person in a skate park? no."], "negative_caption": ["a person is performing a trick on a skateboard. is this person in a skate park? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10466", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000341350.jpg", "positive_caption": ["a desk scene with a chair, computer and monitors. is this a color picture? yes."], "negative_caption": ["a desk scene with a chair, computer and monitors. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2500", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000352073.jpg", "positive_caption": ["the 2 women at the pool are looking at something on the phone. is this pic in color? yes."], "negative_caption": ["the 2 women at the pool are looking at something on the phone. is this pic in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2017", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000294233.jpg", "positive_caption": ["a man riding a surfboard on a wave in the ocean. is this a color picture? yes."], "negative_caption": ["a man riding a surfboard on a wave in the ocean. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3462", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000256270.jpg", "positive_caption": ["a person holding there phone up to take a picture. is this a professional shot? no."], "negative_caption": ["a person holding there phone up to take a picture. is this a professional shot? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4437", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000155262.jpg", "positive_caption": ["this is a group of people playing a game in a park. are they playing baseball? no."], "negative_caption": ["this is a group of people playing a game in a park. are they playing baseball? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1413", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000570259.jpg", "positive_caption": ["the chicken sandwich is next to lettuce, tomato, and a bowl of cole slaw. does this picture appear to be taken at a restaurant? yes."], "negative_caption": ["the chicken sandwich is next to lettuce, tomato, and a bowl of cole slaw. does this picture appear to be taken at a restaurant? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5512", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000453682.jpg", "positive_caption": ["baseball hitter at home base receiving a ball. is this a professional baseball team? yes."], "negative_caption": ["baseball hitter at home base receiving a ball. is this a professional baseball team? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4623", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000115372.jpg", "positive_caption": ["foreign language and cartoon characters painted on a bus. is this a color photo? yes."], "negative_caption": ["foreign language and cartoon characters painted on a bus. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3697", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000412468.jpg", "positive_caption": ["a piece of bread has sprinkles on it. is this cake? no."], "negative_caption": ["a piece of bread has sprinkles on it. is this cake? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_681", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000228783.jpg", "positive_caption": ["a man flying through the air on a pair of skis. is it daytime? yes."], "negative_caption": ["a man flying through the air on a pair of skis. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4206", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000381568.jpg", "positive_caption": ["an ocean with 2 paddle boarders paddling in the waves. is this picture in color? yes."], "negative_caption": ["an ocean with 2 paddle boarders paddling in the waves. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4478", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000065440.jpg", "positive_caption": ["baseball scene of batter in green uniform swinging at pitch. is this in a stadium? yes."], "negative_caption": ["baseball scene of batter in green uniform swinging at pitch. is this in a stadium? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_521", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000088671.jpg", "positive_caption": ["2 dogs playing while their owners sit on stools. is this image in color? yes."], "negative_caption": ["2 dogs playing while their owners sit on stools. is this image in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2301", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000087525.jpg", "positive_caption": ["there are 2 woman playing a video game. is this photo in color? yes."], "negative_caption": ["there are 2 woman playing a video game. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2453", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000375087.jpg", "positive_caption": ["a small bird perched on top of a tree branch. is it in color? yes."], "negative_caption": ["a small bird perched on top of a tree branch. is it in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8795", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000038079.jpg", "positive_caption": ["a bathroom wall, 2 little white square sinks. is this picture in color? no."], "negative_caption": ["a bathroom wall, 2 little white square sinks. is this picture in color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3732", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000088376.jpg", "positive_caption": ["a tankless toilet is installed with a flusher on a back wall a couple feet above it. is this public restroom? no."], "negative_caption": ["a tankless toilet is installed with a flusher on a back wall a couple feet above it. is this public restroom? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5635", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000010526.jpg", "positive_caption": ["a man that is jumping a skateboard outside. is he in a skatepark? no."], "negative_caption": ["a man that is jumping a skateboard outside. is he in a skatepark? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9631", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000467131.jpg", "positive_caption": ["2 adult giraffes and a giraffe calf in front of a rock wall. is this at a zoo? yes."], "negative_caption": ["2 adult giraffes and a giraffe calf in front of a rock wall. is this at a zoo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2637", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000052760.jpg", "positive_caption": ["a black cat is laying on top of a banana. is this a color photo? yes."], "negative_caption": ["a black cat is laying on top of a banana. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5132", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000456481.jpg", "positive_caption": ["a couple sitting at a table having pizza and beverages. are they outside? no."], "negative_caption": ["a couple sitting at a table having pizza and beverages. are they outside? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1958", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000042614.jpg", "positive_caption": ["a baby elephant walking in front of an adult in a barren area. is this in a zoo? no."], "negative_caption": ["a baby elephant walking in front of an adult in a barren area. is this in a zoo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6474", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000298459.jpg", "positive_caption": ["a man with a bandanna on sitting in front of a laptop. is it a color photo? yes."], "negative_caption": ["a man with a bandanna on sitting in front of a laptop. is it a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3423", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000193373.jpg", "positive_caption": ["a man in a wet suit rides a wave on his surf board. can you see what color is his hair? no."], "negative_caption": ["a man in a wet suit rides a wave on his surf board. can you see what color is his hair? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3024", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000479325.jpg", "positive_caption": ["there is a giraffe standing alone on a field. is it a big giraffe? yes."], "negative_caption": ["there is a giraffe standing alone on a field. is it a big giraffe? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2163", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000533039.jpg", "positive_caption": ["1 of the park benches along the water is crushed in. is it daytime? yes."], "negative_caption": ["1 of the park benches along the water is crushed in. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9967", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000098182.jpg", "positive_caption": ["a man plays with a small kid next to a play set. is it a playground? no."], "negative_caption": ["a man plays with a small kid next to a play set. is it a playground? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5731", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000534923.jpg", "positive_caption": ["a open box of pizza placed on a kitchen counter. is this a whole pizza? yes."], "negative_caption": ["a open box of pizza placed on a kitchen counter. is this a whole pizza? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1521", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000519287.jpg", "positive_caption": ["a male paddler boarder goes over an ocean wave. is he going against the direction of the wave? yes."], "negative_caption": ["a male paddler boarder goes over an ocean wave. is he going against the direction of the wave? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4164", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000006160.jpg", "positive_caption": ["a lighted clock on the side of a ship. is this picture in color? no."], "negative_caption": ["a lighted clock on the side of a ship. is this picture in color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3914", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000098689.jpg", "positive_caption": ["2 men playing tennis together on the tennis court. are they on the same team? no."], "negative_caption": ["2 men playing tennis together on the tennis court. are they on the same team? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7013", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000095417.jpg", "positive_caption": ["a man in black shirt riding a skateboard on a sidewalk. is this man facing the camera? no."], "negative_caption": ["a man in black shirt riding a skateboard on a sidewalk. is this man facing the camera? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9219", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000091933.jpg", "positive_caption": ["a wooden table and benches outside on the ground. is it a park? no."], "negative_caption": ["a wooden table and benches outside on the ground. is it a park? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4173", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000435481.jpg", "positive_caption": ["a white train sitting next to a subway platform. is this underground? no."], "negative_caption": ["a white train sitting next to a subway platform. is this underground? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10095", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000479155.jpg", "positive_caption": ["2 young kids interacting in the grocery store produce section. is this a full store? yes."], "negative_caption": ["2 young kids interacting in the grocery store produce section. is this a full store? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10696", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000279221.jpg", "positive_caption": ["a delivery truck at an intersection at night in a city. is this photo in color? yes."], "negative_caption": ["a delivery truck at an intersection at night in a city. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9337", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000170754.jpg", "positive_caption": ["a lady in an orange vest holding a stop ahead sign. is she a older woman? no."], "negative_caption": ["a lady in an orange vest holding a stop ahead sign. is she a older woman? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1142", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000316138.jpg", "positive_caption": ["the man is standing surrounded by motor bikes. is this outside? yes."], "negative_caption": ["the man is standing surrounded by motor bikes. is this outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9919", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000251580.jpg", "positive_caption": ["a young girl is standing with her tennis racket while a man with his tennis racket has a shopping cart full of tennis balls. is it a normal sized shopping cart? yes."], "negative_caption": ["a young girl is standing with her tennis racket while a man with his tennis racket has a shopping cart full of tennis balls. is it a normal sized shopping cart? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9533", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000574077.jpg", "positive_caption": ["a poorly lite ship themed living room. is this a living room? yes."], "negative_caption": ["a poorly lite ship themed living room. is this a living room? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_975", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000168243.jpg", "positive_caption": ["a young woman with dyed hair and sunglasses is holding an umbrella. is it sunny? yes."], "negative_caption": ["a young woman with dyed hair and sunglasses is holding an umbrella. is it sunny? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10973", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000174904.jpg", "positive_caption": ["a christmas ornament in the shape of a bagel hangs from a tree. is this a christmas tree? yes."], "negative_caption": ["a christmas ornament in the shape of a bagel hangs from a tree. is this a christmas tree? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8389", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000136241.jpg", "positive_caption": ["a man with a tie is in a shiny elevator. is this photo in color? yes."], "negative_caption": ["a man with a tie is in a shiny elevator. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3251", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000570013.jpg", "positive_caption": ["a person holding up a red umbrella near a building. is this daytime? yes."], "negative_caption": ["a person holding up a red umbrella near a building. is this daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4806", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000217515.jpg", "positive_caption": ["a group of cows is standing by the water tank. is it a street? no."], "negative_caption": ["a group of cows is standing by the water tank. is it a street? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_512", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000173685.jpg", "positive_caption": ["a river with an older concrete railroad bridge over it. is this color? no."], "negative_caption": ["a river with an older concrete railroad bridge over it. is this color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9504", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000343458.jpg", "positive_caption": ["someone\u2019s hand lifting up the top of a hamburger bun. is it a close up? yes."], "negative_caption": ["someone\u2019s hand lifting up the top of a hamburger bun. is it a close up? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_11105", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000223612.jpg", "positive_caption": ["the overhead view of a railroad track and busy harbor. is it color? yes."], "negative_caption": ["the overhead view of a railroad track and busy harbor. is it color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_965", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000470057.jpg", "positive_caption": ["a black and white picture of a bike locked to a parking meter. is it old? yes."], "negative_caption": ["a black and white picture of a bike locked to a parking meter. is it old? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2027", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000313553.jpg", "positive_caption": ["a lady that is sitting down with a phone. is this picture in color? yes."], "negative_caption": ["a lady that is sitting down with a phone. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1137", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000087070.jpg", "positive_caption": ["a man on snowshoes pulling an evergreen tree over the snow near large trees. is it snowing? no."], "negative_caption": ["a man on snowshoes pulling an evergreen tree over the snow near large trees. is it snowing? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9672", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000214127.jpg", "positive_caption": ["a person in the snow using a snowboard. is it color? yes."], "negative_caption": ["a person in the snow using a snowboard. is it color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8277", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000193954.jpg", "positive_caption": ["set os snowboards laid out on the floor. is there any people in this image? no."], "negative_caption": ["set os snowboards laid out on the floor. is there any people in this image? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3361", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000255950.jpg", "positive_caption": ["looking down on a stony surface shows a bowl with an orange in it and what looks like a large piece of red plastic. is this indoors? no."], "negative_caption": ["looking down on a stony surface shows a bowl with an orange in it and what looks like a large piece of red plastic. is this indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8510", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000151486.jpg", "positive_caption": ["there is a woman taking a bite out of some bread. is she wearing glasses? no."], "negative_caption": ["there is a woman taking a bite out of some bread. is she wearing glasses? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5975", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000577197.jpg", "positive_caption": ["the woman is standing near 1 of 2 large horses. is this a color photo? yes."], "negative_caption": ["the woman is standing near 1 of 2 large horses. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1927", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000031597.jpg", "positive_caption": ["several vases on display behind a glass case. is it outdoors? no."], "negative_caption": ["several vases on display behind a glass case. is it outdoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7450", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000460390.jpg", "positive_caption": ["several people making strokes on a steep ski track. is this photo in color? yes."], "negative_caption": ["several people making strokes on a steep ski track. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10315", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000146586.jpg", "positive_caption": ["a mother zebra and her baby standing beside the road. does the road have cars on it? no."], "negative_caption": ["a mother zebra and her baby standing beside the road. does the road have cars on it? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6235", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000408534.jpg", "positive_caption": ["a person windsurfing on ocean with sky in background. is it a close up picture? no."], "negative_caption": ["a person windsurfing on ocean with sky in background. is it a close up picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7398", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000488785.jpg", "positive_caption": ["a flower pot sitting on a table, during the day. is this outside? no."], "negative_caption": ["a flower pot sitting on a table, during the day. is this outside? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7157", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000133331.jpg", "positive_caption": ["pictures of the australian open picks from first to third. is this golf? no."], "negative_caption": ["pictures of the australian open picks from first to third. is this golf? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6825", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000528098.jpg", "positive_caption": ["the cowboy is playing music on his guitar. is he on stage? no."], "negative_caption": ["the cowboy is playing music on his guitar. is he on stage? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7344", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000314177.jpg", "positive_caption": ["the person is sitting on the unusual toilet in the bathroom. are they using camera phone? no."], "negative_caption": ["the person is sitting on the unusual toilet in the bathroom. are they using camera phone? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10436", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000460461.jpg", "positive_caption": ["a few individuals sitting on benches with skateboards. is it street? no."], "negative_caption": ["a few individuals sitting on benches with skateboards. is it street? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7694", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000033500.jpg", "positive_caption": ["a lady is giving a thumbs up while sitting at a table with pizza and beer. is this a color picture? yes."], "negative_caption": ["a lady is giving a thumbs up while sitting at a table with pizza and beer. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5222", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000523199.jpg", "positive_caption": ["a car stopped at a street light and intersection in front of a 6 floor building. is this a b&w photo? no."], "negative_caption": ["a car stopped at a street light and intersection in front of a 6 floor building. is this a b&w photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4096", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000119799.jpg", "positive_caption": ["a single man standing on skiis in the snow. is he actively skiing? yes."], "negative_caption": ["a single man standing on skiis in the snow. is he actively skiing? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5333", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000135266.jpg", "positive_caption": ["a tall man is talking to a girl while eating. are they sitting down? no."], "negative_caption": ["a tall man is talking to a girl while eating. are they sitting down? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10010", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000104176.jpg", "positive_caption": ["up close head shot of man in a shirt and tie. is he old? no."], "negative_caption": ["up close head shot of man in a shirt and tie. is he old? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10268", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000350549.jpg", "positive_caption": ["a pair of scissors cutting a credit card. can you see hand that's using scissors? no."], "negative_caption": ["a pair of scissors cutting a credit card. can you see hand that's using scissors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_97", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000516205.jpg", "positive_caption": ["a small plate of pizza and some tea. does this display of food look tempting? no."], "negative_caption": ["a small plate of pizza and some tea. does this display of food look tempting? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6957", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000507809.jpg", "positive_caption": ["a kitchen with big tile, a stove and cabinets. is it a modern kitchen? yes."], "negative_caption": ["a kitchen with big tile, a stove and cabinets. is it a modern kitchen? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6415", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000215280.jpg", "positive_caption": ["a pretty lady sitting on a bench in the shade. is she wearing a hat? no."], "negative_caption": ["a pretty lady sitting on a bench in the shade. is she wearing a hat? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5040", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000067222.jpg", "positive_caption": ["a full view of a bedroom with a bed and a chair. is this picture in color? yes."], "negative_caption": ["a full view of a bedroom with a bed and a chair. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4717", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000273321.jpg", "positive_caption": ["guy jumps up to catch the frisbee in the gym. is this outside? no."], "negative_caption": ["guy jumps up to catch the frisbee in the gym. is this outside? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8109", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000247166.jpg", "positive_caption": ["several men flying kites with skyscrapers in the background. are they on a hill? no."], "negative_caption": ["several men flying kites with skyscrapers in the background. are they on a hill? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_597", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000125374.jpg", "positive_caption": ["a person wearing red pants and goggles while riding a ski. is this a man? yes."], "negative_caption": ["a person wearing red pants and goggles while riding a ski. is this a man? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1581", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000302661.jpg", "positive_caption": ["2 large sheep are and a dog and 1 of the sheep is eating out of a bowl. do they all have food? no."], "negative_caption": ["2 large sheep are and a dog and 1 of the sheep is eating out of a bowl. do they all have food? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_389", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000501379.jpg", "positive_caption": ["a large white truck on a city street. is this a trash truck? no."], "negative_caption": ["a large white truck on a city street. is this a trash truck? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10988", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000534391.jpg", "positive_caption": ["a baseball player swinging a bat at a baseball. is this picture in color? yes."], "negative_caption": ["a baseball player swinging a bat at a baseball. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3783", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000372349.jpg", "positive_caption": ["a man and a woman in a river. are they swimming? no."], "negative_caption": ["a man and a woman in a river. are they swimming? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8672", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000205604.jpg", "positive_caption": ["a baseball player swinging at a pitch, with a runner on third. are they at actual baseball field? no."], "negative_caption": ["a baseball player swinging at a pitch, with a runner on third. are they at actual baseball field? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3824", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000435343.jpg", "positive_caption": ["a man riding the waves in shallow surf. is this picture in color? yes."], "negative_caption": ["a man riding the waves in shallow surf. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1945", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000310538.jpg", "positive_caption": ["a man that is standing on a tennis court with a racquet. is this photo in color? yes."], "negative_caption": ["a man that is standing on a tennis court with a racquet. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10115", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000245642.jpg", "positive_caption": ["a view from a bicycle on a small road with many sheep in front. is it in color? yes."], "negative_caption": ["a view from a bicycle on a small road with many sheep in front. is it in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10165", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000569017.jpg", "positive_caption": ["people on the beach while a boat comes in to the pier. is this picture in color? yes."], "negative_caption": ["people on the beach while a boat comes in to the pier. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1464", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000581317.jpg", "positive_caption": ["woman in purple shirt examines her cellphone in the open field. is it big field? yes."], "negative_caption": ["woman in purple shirt examines her cellphone in the open field. is it big field? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10167", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000277267.jpg", "positive_caption": ["a person getting his haircut sitting next to a person looking at camera. is it daytime in image? yes."], "negative_caption": ["a person getting his haircut sitting next to a person looking at camera. is it daytime in image? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5205", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000526671.jpg", "positive_caption": ["a white and black cat and a brown and white dog. is this a professional photo? no."], "negative_caption": ["a white and black cat and a brown and white dog. is this a professional photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3320", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000031392.jpg", "positive_caption": ["grey cat on dashboard of moving car on highway. are they little kittens? no."], "negative_caption": ["grey cat on dashboard of moving car on highway. are they little kittens? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8904", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000271546.jpg", "positive_caption": ["2 men with tennis rackets on a grass playing court. are they playing doubles? no."], "negative_caption": ["2 men with tennis rackets on a grass playing court. are they playing doubles? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7981", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000522454.jpg", "positive_caption": ["pair of elephant with man in large grassy field near mountain. is this a zoo? no."], "negative_caption": ["pair of elephant with man in large grassy field near mountain. is this a zoo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6613", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000576820.jpg", "positive_caption": ["a line of people checking in their luggage at an airport. can you tell what airport this is? no."], "negative_caption": ["a line of people checking in their luggage at an airport. can you tell what airport this is? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7794", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000471096.jpg", "positive_caption": ["3 elephants are submerged up to the tops of their trunks within a narrow body of water that is lined with rocks and vegetation. is it a color photo? yes."], "negative_caption": ["3 elephants are submerged up to the tops of their trunks within a narrow body of water that is lined with rocks and vegetation. is it a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5687", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000408989.jpg", "positive_caption": ["a woman in a gray tank pours tomatoes into a blender. is this a color photo? yes."], "negative_caption": ["a woman in a gray tank pours tomatoes into a blender. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8656", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000021400.jpg", "positive_caption": ["a man walking next to a girl holding a pink umbrella. is this indoors? no."], "negative_caption": ["a man walking next to a girl holding a pink umbrella. is this indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7220", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000305557.jpg", "positive_caption": ["a man with a toothbrush in his mouth with foam coming out. is the man in his pajamas? no."], "negative_caption": ["a man with a toothbrush in his mouth with foam coming out. is the man in his pajamas? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3356", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000517069.jpg", "positive_caption": ["2 women waiting at a bench next to a street. is it in color? yes."], "negative_caption": ["2 women waiting at a bench next to a street. is it in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7622", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000286660.jpg", "positive_caption": ["a young woman is hugging a weird teddy bear. is she old? no."], "negative_caption": ["a young woman is hugging a weird teddy bear. is she old? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10150", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000192298.jpg", "positive_caption": ["a dog wearing a christmas hat, opened presents in the background. is it a small dog? no."], "negative_caption": ["a dog wearing a christmas hat, opened presents in the background. is it a small dog? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6598", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000301762.jpg", "positive_caption": ["creamy golden batter being stirred by a spatula. is this a close up? yes."], "negative_caption": ["creamy golden batter being stirred by a spatula. is this a close up? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8287", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000087151.jpg", "positive_caption": ["a young girl holding a wii controller setting on a chair. is it indoors? yes."], "negative_caption": ["a young girl holding a wii controller setting on a chair. is it indoors? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6051", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000252043.jpg", "positive_caption": ["a model kitchen is shown with white appliances. is this a new modern kitchen? yes."], "negative_caption": ["a model kitchen is shown with white appliances. is this a new modern kitchen? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1268", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000265444.jpg", "positive_caption": ["a train drives down a track in the woods. is it a passenger train? yes."], "negative_caption": ["a train drives down a track in the woods. is it a passenger train? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4109", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000093644.jpg", "positive_caption": ["a woman and her son using an old imac computer. are they same gender? no."], "negative_caption": ["a woman and her son using an old imac computer. are they same gender? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5907", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000351553.jpg", "positive_caption": ["luggage, all shapes, sizes and colors are stacked in a room. is this in an airport? no."], "negative_caption": ["luggage, all shapes, sizes and colors are stacked in a room. is this in an airport? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_613", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000310104.jpg", "positive_caption": ["a man running with a tennis racket in his hand. is he on a tennis court? no."], "negative_caption": ["a man running with a tennis racket in his hand. is he on a tennis court? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7047", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000328862.jpg", "positive_caption": ["a close up look at a very big white fridge and some cabinets. is this photo in color? yes."], "negative_caption": ["a close up look at a very big white fridge and some cabinets. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10091", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000520950.jpg", "positive_caption": ["the kitchen is full of spices on the rack. is this in a kitchen? yes."], "negative_caption": ["the kitchen is full of spices on the rack. is this in a kitchen? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6828", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000061658.jpg", "positive_caption": ["a mixture of broccoli and cauliflower on a white platter. is there dressing on this food? no."], "negative_caption": ["a mixture of broccoli and cauliflower on a white platter. is there dressing on this food? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9935", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000256613.jpg", "positive_caption": ["the inside of a room with green painted walls and a window that has a clock and a photo of a man above it. is it a color photo? yes."], "negative_caption": ["the inside of a room with green painted walls and a window that has a clock and a photo of a man above it. is it a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6124", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000114185.jpg", "positive_caption": ["2 men in trench coats and ties walk down a sidewalk. is this a busy street? yes."], "negative_caption": ["2 men in trench coats and ties walk down a sidewalk. is this a busy street? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6838", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000324916.jpg", "positive_caption": ["3 urinals on a tiled wall with colored glass on the window. is there anyone in this bathroom? no."], "negative_caption": ["3 urinals on a tiled wall with colored glass on the window. is there anyone in this bathroom? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_283", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000152209.jpg", "positive_caption": ["a white sink with a mirror above it next to a small toilet. is it a professional photo? no."], "negative_caption": ["a white sink with a mirror above it next to a small toilet. is it a professional photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1097", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000084170.jpg", "positive_caption": ["a bus driving on a rain covered street. is it a double decker? no."], "negative_caption": ["a bus driving on a rain covered street. is it a double decker? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8536", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000046544.jpg", "positive_caption": ["a woman swings a racket at a tennis ball. is this on a court? yes."], "negative_caption": ["a woman swings a racket at a tennis ball. is this on a court? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4502", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000499423.jpg", "positive_caption": ["a very tall church tower with a clock on the side of it. is this image in color? yes."], "negative_caption": ["a very tall church tower with a clock on the side of it. is this image in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9751", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000177939.jpg", "positive_caption": ["a pan that has broccoli and meat cooking in it. is this a frying pan? yes."], "negative_caption": ["a pan that has broccoli and meat cooking in it. is this a frying pan? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6569", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000080517.jpg", "positive_caption": ["the person is leaning over the green bananas. is this outside? yes."], "negative_caption": ["the person is leaning over the green bananas. is this outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10989", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000231381.jpg", "positive_caption": ["brown bears in a green field in spring time. ie it big field? yes."], "negative_caption": ["brown bears in a green field in spring time. ie it big field? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1254", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000565878.jpg", "positive_caption": ["darkly lit photo of man with hotdog in front of street view window. does it look like nighttime? no."], "negative_caption": ["darkly lit photo of man with hotdog in front of street view window. does it look like nighttime? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4082", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000383065.jpg", "positive_caption": ["a public restroom facility on the side walk. is it raining? no."], "negative_caption": ["a public restroom facility on the side walk. is it raining? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7279", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000183980.jpg", "positive_caption": ["a mouse sitting on top of a keyboard with paper underneath. is it a cartoon mouse? no."], "negative_caption": ["a mouse sitting on top of a keyboard with paper underneath. is it a cartoon mouse? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4284", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000417481.jpg", "positive_caption": ["black and white image of a man wearing a motorcycle helmet. is he on a motorcycle? no."], "negative_caption": ["black and white image of a man wearing a motorcycle helmet. is he on a motorcycle? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_11044", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000337814.jpg", "positive_caption": ["2 people are playing wii boxing in a room. can you see game they are playing? no."], "negative_caption": ["2 people are playing wii boxing in a room. can you see game they are playing? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7884", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000480408.jpg", "positive_caption": ["a man wearing a hat while riding a horse. is it indoors? no."], "negative_caption": ["a man wearing a hat while riding a horse. is it indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10861", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000095999.jpg", "positive_caption": ["a army plane parked as people take pictures. is this a vintage plane? yes."], "negative_caption": ["a army plane parked as people take pictures. is this a vintage plane? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3895", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000573536.jpg", "positive_caption": ["a man with a shaved head talking to a woman. are they outdoors? no."], "negative_caption": ["a man with a shaved head talking to a woman. are they outdoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8544", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000286639.jpg", "positive_caption": ["white square plate full of different kinds of food. is it a paper plate? no."], "negative_caption": ["white square plate full of different kinds of food. is it a paper plate? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6458", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000083635.jpg", "positive_caption": ["a baseball player throwing a baseball during a game. is this a professional game? yes."], "negative_caption": ["a baseball player throwing a baseball during a game. is this a professional game? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_490", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000010230.jpg", "positive_caption": ["a baseball player holding a ball while standing on a field. is this a baseball field? yes."], "negative_caption": ["a baseball player holding a ball while standing on a field. is this a baseball field? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5320", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000277389.jpg", "positive_caption": ["the man is pitching the baseball during the game. is he in a stadium? yes."], "negative_caption": ["the man is pitching the baseball during the game. is he in a stadium? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5294", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000270460.jpg", "positive_caption": ["colorful japanese parasols of silk painted with birds and flowers. is this indoors? no."], "negative_caption": ["colorful japanese parasols of silk painted with birds and flowers. is this indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3762", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000066345.jpg", "positive_caption": ["a male tennis player in action on the court. is he wearing glasses? no."], "negative_caption": ["a male tennis player in action on the court. is he wearing glasses? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1288", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000105192.jpg", "positive_caption": ["a cat walking next to a bicycle outside. is it color? yes."], "negative_caption": ["a cat walking next to a bicycle outside. is it color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2370", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000224971.jpg", "positive_caption": ["a view of a bunch of food on a counter top. is this in a kitchen? yes."], "negative_caption": ["a view of a bunch of food on a counter top. is this in a kitchen? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_955", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000015016.jpg", "positive_caption": ["a white bird with black tipped wings glides in the pale blue sky. is this a penguin? no."], "negative_caption": ["a white bird with black tipped wings glides in the pale blue sky. is this a penguin? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1886", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000432891.jpg", "positive_caption": ["a baseball game with a hitter running from home plate and a catcher and umpire looking up into the air. is this a professional game? no."], "negative_caption": ["a baseball game with a hitter running from home plate and a catcher and umpire looking up into the air. is this a professional game? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_536", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000095155.jpg", "positive_caption": ["4 photographs of a person in red jacket snowboarding. is this a collage of pictures? yes."], "negative_caption": ["4 photographs of a person in red jacket snowboarding. is this a collage of pictures? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10559", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000346905.jpg", "positive_caption": ["a little elephant stands between 2 large, tusked elephants. are they in water? no."], "negative_caption": ["a little elephant stands between 2 large, tusked elephants. are they in water? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10726", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000246700.jpg", "positive_caption": ["a big thomas the train replica sits parked on display. is anyone in this image? no."], "negative_caption": ["a big thomas the train replica sits parked on display. is anyone in this image? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2765", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000287959.jpg", "positive_caption": ["this cross section of a sandwich is still wrapped. is it in color? yes."], "negative_caption": ["this cross section of a sandwich is still wrapped. is it in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10923", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000311361.jpg", "positive_caption": ["an old family picture each family member has a flower pinned to the clothes. is it old like black and white old? yes."], "negative_caption": ["an old family picture each family member has a flower pinned to the clothes. is it old like black and white old? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2091", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000569333.jpg", "positive_caption": ["a black and white cat on a purple bed looking at a blue swiss army knife. is this an adult? yes."], "negative_caption": ["a black and white cat on a purple bed looking at a blue swiss army knife. is this an adult? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9835", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000257443.jpg", "positive_caption": ["a tennis player playing tennis on the tennis court. is this indoors? no."], "negative_caption": ["a tennis player playing tennis on the tennis court. is this indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7267", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000517341.jpg", "positive_caption": ["a train passes by a freshly cut field. is this picture in color? yes."], "negative_caption": ["a train passes by a freshly cut field. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_478", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000269621.jpg", "positive_caption": ["a couple of giraffe standing next to each other. are they the same height? no."], "negative_caption": ["a couple of giraffe standing next to each other. are they the same height? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_45", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000236224.jpg", "positive_caption": ["a night city scene is lit up with cars and busses. is it a big city? yes."], "negative_caption": ["a night city scene is lit up with cars and busses. is it a big city? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5312", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000175855.jpg", "positive_caption": ["3 people shown around a birthday cake which has just been lit. is this photo in color? yes."], "negative_caption": ["3 people shown around a birthday cake which has just been lit. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4642", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000084479.jpg", "positive_caption": ["a dog stating in the sidecar of a motorcycle. is this photo in color? no."], "negative_caption": ["a dog stating in the sidecar of a motorcycle. is this photo in color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5349", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000005339.jpg", "positive_caption": ["surfer in black wet suit riding a wave. is he the only surfer? yes."], "negative_caption": ["surfer in black wet suit riding a wave. is he the only surfer? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_832", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000446864.jpg", "positive_caption": ["a bowl of strawberries beside a platter of vegetables. is this photo in color? yes."], "negative_caption": ["a bowl of strawberries beside a platter of vegetables. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4376", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000324332.jpg", "positive_caption": ["2 men and 2 woman boarding a bus. either of these people wearing glasses? no."], "negative_caption": ["2 men and 2 woman boarding a bus. either of these people wearing glasses? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3863", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000501116.jpg", "positive_caption": ["a red light slanted at a very strange angle. is this a traffic light? yes."], "negative_caption": ["a red light slanted at a very strange angle. is this a traffic light? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10097", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000071621.jpg", "positive_caption": ["a white toilet sitting under a toilet seat protector. is this in a bathroom? yes."], "negative_caption": ["a white toilet sitting under a toilet seat protector. is this in a bathroom? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3851", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000556637.jpg", "positive_caption": ["a man eating a muffin outdoors by a building. is this picture in color? yes."], "negative_caption": ["a man eating a muffin outdoors by a building. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2613", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000109924.jpg", "positive_caption": ["5 separate cakes made into a train birthday cake. how the cake have anything writing on it? yes."], "negative_caption": ["5 separate cakes made into a train birthday cake. how the cake have anything writing on it? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10733", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000263762.jpg", "positive_caption": ["2 buses passing each other on a city street. is it a busy street? no."], "negative_caption": ["2 buses passing each other on a city street. is it a busy street? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3806", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000228318.jpg", "positive_caption": ["orange and white cat tail on a computer keyboard. is this a color picture? yes."], "negative_caption": ["orange and white cat tail on a computer keyboard. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1228", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000297510.jpg", "positive_caption": ["a train traveling down tracks next to a forest. is this a color picture? yes."], "negative_caption": ["a train traveling down tracks next to a forest. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3909", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000500330.jpg", "positive_caption": ["the microwave is next to the dish washer underneath the counter. is this photo in color? yes."], "negative_caption": ["the microwave is next to the dish washer underneath the counter. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10351", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000311232.jpg", "positive_caption": ["a small train is seen coming down the tracks. is this picture in color? yes."], "negative_caption": ["a small train is seen coming down the tracks. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4920", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000406608.jpg", "positive_caption": ["girl in bikini walks through water holding her surfboard. is it very sunny? yes."], "negative_caption": ["girl in bikini walks through water holding her surfboard. is it very sunny? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4654", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000425864.jpg", "positive_caption": ["a shiny maroon bus rounds the corner on a city street. is it an american city? no."], "negative_caption": ["a shiny maroon bus rounds the corner on a city street. is it an american city? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4301", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000076082.jpg", "positive_caption": ["old city street with people commuting holding umbrella. is this photo in color? no."], "negative_caption": ["old city street with people commuting holding umbrella. is this photo in color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9106", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000558169.jpg", "positive_caption": ["a blue bird sitting on someone's arm in a room. is this indoors? yes."], "negative_caption": ["a blue bird sitting on someone's arm in a room. is this indoors? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8761", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000575625.jpg", "positive_caption": ["a close up of a hot dog with onions. is it a big hot dog? yes."], "negative_caption": ["a close up of a hot dog with onions. is it a big hot dog? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_11089", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000085029.jpg", "positive_caption": ["a banana bunch for sale and people looking. is this outside market? yes."], "negative_caption": ["a banana bunch for sale and people looking. is this outside market? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8489", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000104328.jpg", "positive_caption": ["several of the baseball players are in view. are they playing baseball? yes."], "negative_caption": ["several of the baseball players are in view. are they playing baseball? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2489", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000336426.jpg", "positive_caption": ["the young woman is skiing on the lake. is she in the water? yes."], "negative_caption": ["the young woman is skiing on the lake. is she in the water? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1793", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000168811.jpg", "positive_caption": ["a crowd of people take pictures of a departing train. is this at a train station? yes."], "negative_caption": ["a crowd of people take pictures of a departing train. is this at a train station? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9409", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000239120.jpg", "positive_caption": ["a bowl of food sits next to a glass of tea. can you tell what kind of tea it is? no."], "negative_caption": ["a bowl of food sits next to a glass of tea. can you tell what kind of tea it is? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_147", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000492638.jpg", "positive_caption": ["2 men in sweaters standing next to each other in a house. is this bathroom? no."], "negative_caption": ["2 men in sweaters standing next to each other in a house. is this bathroom? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3681", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000124122.jpg", "positive_caption": ["a girl stretches her legs above her head while a cat and dog look on. is this a color photo? no."], "negative_caption": ["a girl stretches her legs above her head while a cat and dog look on. is this a color photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4359", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000314224.jpg", "positive_caption": ["a man sitting on his motorcycle by the grass. is this picture in color? yes."], "negative_caption": ["a man sitting on his motorcycle by the grass. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6938", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000181475.jpg", "positive_caption": ["a baby eats a meal with someone else and a stuffed bear. is he eating with a parent? yes."], "negative_caption": ["a baby eats a meal with someone else and a stuffed bear. is he eating with a parent? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4528", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000077360.jpg", "positive_caption": ["there is a white cow bull in front of a white building with purple trim. is this a farm? no."], "negative_caption": ["there is a white cow bull in front of a white building with purple trim. is this a farm? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10376", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000396080.jpg", "positive_caption": ["cars traveling down a street under a traffic light. does it look like a city street? yes."], "negative_caption": ["cars traveling down a street under a traffic light. does it look like a city street? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7117", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000140020.jpg", "positive_caption": ["a man standing under a large clock tower next to the ocean. is this a painting? no."], "negative_caption": ["a man standing under a large clock tower next to the ocean. is this a painting? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8774", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000512702.jpg", "positive_caption": ["a skateboarding man is on a half pipe. does he wear a helmet? no."], "negative_caption": ["a skateboarding man is on a half pipe. does he wear a helmet? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6881", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000569450.jpg", "positive_caption": ["a stove with pan and teapot on top in the kitchen. is this a color picture? yes."], "negative_caption": ["a stove with pan and teapot on top in the kitchen. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10145", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000151375.jpg", "positive_caption": ["a statue of a man with a beard has a bowl between his legs that is filled with bananas. is this a famous statue? no."], "negative_caption": ["a statue of a man with a beard has a bowl between his legs that is filled with bananas. is this a famous statue? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1823", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000578331.jpg", "positive_caption": ["2 women who have painted on mustaches petting a horse. are they wearing hats? no."], "negative_caption": ["2 women who have painted on mustaches petting a horse. are they wearing hats? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3687", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000361811.jpg", "positive_caption": ["a white tub sits in the middle of room in the house. is it in the bathroom? no."], "negative_caption": ["a white tub sits in the middle of room in the house. is it in the bathroom? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3343", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000088168.jpg", "positive_caption": ["asian guy on a moped and smoking a cigarette. is he wearing a helmet? no."], "negative_caption": ["asian guy on a moped and smoking a cigarette. is he wearing a helmet? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8350", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000073626.jpg", "positive_caption": ["a crowded city street filled with people carrying umbrellas. is it raining? no."], "negative_caption": ["a crowded city street filled with people carrying umbrellas. is it raining? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1858", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000152286.jpg", "positive_caption": ["a man throwing a baseball away from him. is this photo in color? yes."], "negative_caption": ["a man throwing a baseball away from him. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1342", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000047781.jpg", "positive_caption": ["the hotel bed is designed for the business traveler. it is picture color? yes."], "negative_caption": ["the hotel bed is designed for the business traveler. it is picture color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10925", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000043635.jpg", "positive_caption": ["a bunch of people sit in an open court yard. is this picture in color? yes."], "negative_caption": ["a bunch of people sit in an open court yard. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8515", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000017778.jpg", "positive_caption": ["a hummingbird flying above a bunch of small red and white flowers. is it raining? no."], "negative_caption": ["a hummingbird flying above a bunch of small red and white flowers. is it raining? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7477", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000181322.jpg", "positive_caption": ["several white boats in some water near some trees. are there boats in this? yes."], "negative_caption": ["several white boats in some water near some trees. are there boats in this? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1621", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000097981.jpg", "positive_caption": ["the old toilet is sitting on the sidewalk with newspaper on it. is this a color photo? yes."], "negative_caption": ["the old toilet is sitting on the sidewalk with newspaper on it. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6592", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000290416.jpg", "positive_caption": ["a person that is skiing in the air in the snow. is this photo in color? yes."], "negative_caption": ["a person that is skiing in the air in the snow. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8739", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000210643.jpg", "positive_caption": ["a selection of food with toothpicks sits on a plate. are they fruits? no."], "negative_caption": ["a selection of food with toothpicks sits on a plate. are they fruits? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3281", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000363145.jpg", "positive_caption": ["a corner of a rest room with tiled walls and a big mirror. does it look like a public bathroom? no."], "negative_caption": ["a corner of a rest room with tiled walls and a big mirror. does it look like a public bathroom? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5414", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000131339.jpg", "positive_caption": ["a man is riding waves on a surboard. is he in a wetsuit? no."], "negative_caption": ["a man is riding waves on a surboard. is he in a wetsuit? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1796", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000070211.jpg", "positive_caption": ["the remains of a large, lavishly decorated cake on an office desk. is it a birthday cake? yes."], "negative_caption": ["the remains of a large, lavishly decorated cake on an office desk. is it a birthday cake? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4853", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000321085.jpg", "positive_caption": ["there is a boat that is going down the river. is it a fishing boat? no."], "negative_caption": ["there is a boat that is going down the river. is it a fishing boat? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8996", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000555391.jpg", "positive_caption": ["the stairs lead to a balcony with tables with umbrellas over them. is this a restaurant setting? no."], "negative_caption": ["the stairs lead to a balcony with tables with umbrellas over them. is this a restaurant setting? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1297", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000140976.jpg", "positive_caption": ["a toy airplane made out of some metal. is this a color picture? yes."], "negative_caption": ["a toy airplane made out of some metal. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5127", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000318219.jpg", "positive_caption": ["a young boy stares up at the computer monitor. is this picture in color? yes."], "negative_caption": ["a young boy stares up at the computer monitor. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10503", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000021676.jpg", "positive_caption": ["2 men holding the back door of a car open. is this the trunk? no."], "negative_caption": ["2 men holding the back door of a car open. is this the trunk? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4578", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000176621.jpg", "positive_caption": ["a building with an advert for a musical on the front. is this downtown? yes."], "negative_caption": ["a building with an advert for a musical on the front. is this downtown? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1999", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000418397.jpg", "positive_caption": ["a baseball player with a bat in the batters box. is this a pro game? yes."], "negative_caption": ["a baseball player with a bat in the batters box. is this a pro game? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_991", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000531045.jpg", "positive_caption": ["a bathroom inside an airplane with 2 rolls of toilet paper near the open toilet. is there bus in this picture? no."], "negative_caption": ["a bathroom inside an airplane with 2 rolls of toilet paper near the open toilet. is there bus in this picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5602", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000506058.jpg", "positive_caption": ["there are man and woman smiling on a pic. are they hugging each other? no."], "negative_caption": ["there are man and woman smiling on a pic. are they hugging each other? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_773", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000240762.jpg", "positive_caption": ["man and woman in a speeding motor boat on calm water. is it sunny? yes."], "negative_caption": ["man and woman in a speeding motor boat on calm water. is it sunny? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4017", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000507516.jpg", "positive_caption": ["a pizza is cooked on a barbecue grill. is this indoors? no."], "negative_caption": ["a pizza is cooked on a barbecue grill. is this indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4627", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000164135.jpg", "positive_caption": ["a young man riding a skateboard down a curvy sidewalk. is he at a skatepark? no."], "negative_caption": ["a young man riding a skateboard down a curvy sidewalk. is he at a skatepark? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10028", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000481168.jpg", "positive_caption": ["a girl hitting a tennis ball with a tennis racket. is she an adult? no."], "negative_caption": ["a girl hitting a tennis ball with a tennis racket. is she an adult? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7069", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000352841.jpg", "positive_caption": ["a glass front cabinet displays a messy assortment of non matching glasses. is this a kitchen? yes."], "negative_caption": ["a glass front cabinet displays a messy assortment of non matching glasses. is this a kitchen? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5642", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000015897.jpg", "positive_caption": ["a woman that is holding a stuffed bear. is this a blonde woman? no."], "negative_caption": ["a woman that is holding a stuffed bear. is this a blonde woman? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7130", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000473733.jpg", "positive_caption": ["a skateboarder pulling tricks in a skateboard park. is it daytime? yes."], "negative_caption": ["a skateboarder pulling tricks in a skateboard park. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5270", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000136461.jpg", "positive_caption": ["a bus passing through a 4 way intersection with traffic light. is it a school bus? no."], "negative_caption": ["a bus passing through a 4 way intersection with traffic light. is it a school bus? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6564", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000433825.jpg", "positive_caption": ["a busy city street has items for sale and bike traffic. is this like a market? yes."], "negative_caption": ["a busy city street has items for sale and bike traffic. is this like a market? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4901", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000144000.jpg", "positive_caption": ["there is a baseball game in progress in a stadium. is it day time? yes."], "negative_caption": ["there is a baseball game in progress in a stadium. is it day time? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4518", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000441116.jpg", "positive_caption": ["there is a red train that is stopped at the platform. is it a passenger train? yes."], "negative_caption": ["there is a red train that is stopped at the platform. is it a passenger train? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6952", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000371054.jpg", "positive_caption": ["an old pickup truck sits outside among other classic cars. is this at a car show? yes."], "negative_caption": ["an old pickup truck sits outside among other classic cars. is this at a car show? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8937", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000156768.jpg", "positive_caption": ["a plane is flying in the night sly. is it a modern photo? yes."], "negative_caption": ["a plane is flying in the night sly. is it a modern photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_946", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000446615.jpg", "positive_caption": ["a black and white cat lays on a bed. any animals besides that cat? no."], "negative_caption": ["a black and white cat lays on a bed. any animals besides that cat? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3908", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000364913.jpg", "positive_caption": ["a mamma sheep with her 2 babies laying in the grass. is this picture in color? yes."], "negative_caption": ["a mamma sheep with her 2 babies laying in the grass. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6038", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000075359.jpg", "positive_caption": ["a chair made out of skis sitting in the grass. is it sunny outside? yes."], "negative_caption": ["a chair made out of skis sitting in the grass. is it sunny outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7111", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000039509.jpg", "positive_caption": ["2 people lay on the beach under umbrellas facing the water. is it daytime? yes."], "negative_caption": ["2 people lay on the beach under umbrellas facing the water. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_51", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000075456.jpg", "positive_caption": ["a pizza with canadian bacon and pineapple in a fluted pan. is this a color picture? yes."], "negative_caption": ["a pizza with canadian bacon and pineapple in a fluted pan. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9889", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000387567.jpg", "positive_caption": ["an image of a person slicing pizza with a knife. is it pepperoni pizza? no."], "negative_caption": ["an image of a person slicing pizza with a knife. is it pepperoni pizza? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9270", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000276694.jpg", "positive_caption": ["a room with a desk, 2 chairs and 2 beds. is it in color? yes."], "negative_caption": ["a room with a desk, 2 chairs and 2 beds. is it in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1889", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000181566.jpg", "positive_caption": ["a black bird standing on a wooden frame. is that the only visible bird? yes."], "negative_caption": ["a black bird standing on a wooden frame. is that the only visible bird? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6624", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000324971.jpg", "positive_caption": ["a female surfer is riding through the wave. is she wearing a wetsuit? no."], "negative_caption": ["a female surfer is riding through the wave. is she wearing a wetsuit? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2014", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000363202.jpg", "positive_caption": ["2 women hold a knife above the heart shaped cake. does the cake have any writing on it? no."], "negative_caption": ["2 women hold a knife above the heart shaped cake. does the cake have any writing on it? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3260", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000130908.jpg", "positive_caption": ["a large red and white bus going down a road. is it a double decker bus? no."], "negative_caption": ["a large red and white bus going down a road. is it a double decker bus? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1063", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000114203.jpg", "positive_caption": ["2 giraffes and 3 zebras standing in an enclosure. is this in a zoo? yes."], "negative_caption": ["2 giraffes and 3 zebras standing in an enclosure. is this in a zoo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_908", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000334244.jpg", "positive_caption": ["a 3 story building with a clock on top. it is color picture? yes."], "negative_caption": ["a 3 story building with a clock on top. it is color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7873", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000190227.jpg", "positive_caption": ["a toilet made of metal sits next to a window. is this image in color? yes."], "negative_caption": ["a toilet made of metal sits next to a window. is this image in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10463", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000519565.jpg", "positive_caption": ["2 adults and a baby sit on a bench. is this indoors? no."], "negative_caption": ["2 adults and a baby sit on a bench. is this indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7649", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000511480.jpg", "positive_caption": ["the train pulls into a stop on a very snowy day. can you see any people in this picture? no."], "negative_caption": ["the train pulls into a stop on a very snowy day. can you see any people in this picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1049", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000303761.jpg", "positive_caption": ["small giraffe spitting out water in front of a large giraffe. are they outside? yes."], "negative_caption": ["small giraffe spitting out water in front of a large giraffe. are they outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2311", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000203615.jpg", "positive_caption": ["there are a few ducks that are sitting in the river. is it daytime? yes."], "negative_caption": ["there are a few ducks that are sitting in the river. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3385", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000498969.jpg", "positive_caption": ["a street sign in a cluster of bushes next to a building. can you tell what kind of building this is? no."], "negative_caption": ["a street sign in a cluster of bushes next to a building. can you tell what kind of building this is? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2544", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000211641.jpg", "positive_caption": ["2 park benches near jettied ocean inlet filled with boats. is this a marina? yes."], "negative_caption": ["2 park benches near jettied ocean inlet filled with boats. is this a marina? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6402", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000315824.jpg", "positive_caption": ["there is a bear that is stiing on the ground. is this daytime? yes."], "negative_caption": ["there is a bear that is stiing on the ground. is this daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9951", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000337297.jpg", "positive_caption": ["2 large giraffes out in the sun. are both giraffes full grown? yes."], "negative_caption": ["2 large giraffes out in the sun. are both giraffes full grown? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5932", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000537689.jpg", "positive_caption": ["a male with a beard and a woman in a dress. are they a couple? no."], "negative_caption": ["a male with a beard and a woman in a dress. are they a couple? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3991", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000374185.jpg", "positive_caption": ["a little boy in the sand flying a kite. is it a beach? no."], "negative_caption": ["a little boy in the sand flying a kite. is it a beach? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6873", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000459543.jpg", "positive_caption": ["3 men riding on top of a motorcycle. is this some kind of act? yes."], "negative_caption": ["3 men riding on top of a motorcycle. is this some kind of act? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1904", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000096222.jpg", "positive_caption": ["a man in a black t-shirt stands in front of a birthday cake in a kitchen. is this a color picture? yes."], "negative_caption": ["a man in a black t-shirt stands in front of a birthday cake in a kitchen. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5148", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000085876.jpg", "positive_caption": ["a young boy swings his tennis racket on the court. is this a color photo? yes."], "negative_caption": ["a young boy swings his tennis racket on the court. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_565", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000262935.jpg", "positive_caption": ["a man in a red and gray snow outfit stands on skis holding his ski poles as he stands near other skiers and snowboarders. is he wearing a hat? yes."], "negative_caption": ["a man in a red and gray snow outfit stands on skis holding his ski poles as he stands near other skiers and snowboarders. is he wearing a hat? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6214", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000166631.jpg", "positive_caption": ["a large grey elephant being ridden down a busy highway. is it a dirt road? no."], "negative_caption": ["a large grey elephant being ridden down a busy highway. is it a dirt road? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_219", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000224629.jpg", "positive_caption": ["a couple of beautiful women standing on either side of a server. are they dressed casual? yes."], "negative_caption": ["a couple of beautiful women standing on either side of a server. are they dressed casual? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5335", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000077643.jpg", "positive_caption": ["a floral display is shown on the street corner. is this the picture a flower shop? no."], "negative_caption": ["a floral display is shown on the street corner. is this the picture a flower shop? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3916", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000479191.jpg", "positive_caption": ["a tray topped with 2 slices of cake and 2 drinks. does this look like wedding cake? no."], "negative_caption": ["a tray topped with 2 slices of cake and 2 drinks. does this look like wedding cake? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6517", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000237308.jpg", "positive_caption": ["the long train has a yellow and red engine and moves down the track. is this a passenger train? no."], "negative_caption": ["the long train has a yellow and red engine and moves down the track. is this a passenger train? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9640", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000410155.jpg", "positive_caption": ["a group of men wearing ties posing for a photo. is this a color picture? yes."], "negative_caption": ["a group of men wearing ties posing for a photo. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3767", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000396574.jpg", "positive_caption": ["a woman sitting curled up in a suit case. is she inside the suitcase? yes."], "negative_caption": ["a woman sitting curled up in a suit case. is she inside the suitcase? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3188", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000202829.jpg", "positive_caption": ["donuts and brownies on display in a store. are they drinking dunkin donut cups? no."], "negative_caption": ["donuts and brownies on display in a store. are they drinking dunkin donut cups? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2179", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000034795.jpg", "positive_caption": ["a man and a group of people playing wii in their living room. are they college students? no."], "negative_caption": ["a man and a group of people playing wii in their living room. are they college students? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5893", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000088117.jpg", "positive_caption": ["a brown dog covered with sheet while sleeping on a bed. is it a dog bed? no."], "negative_caption": ["a brown dog covered with sheet while sleeping on a bed. is it a dog bed? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2852", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000231958.jpg", "positive_caption": ["a group of people flying kites on a field. is this photo in color? yes."], "negative_caption": ["a group of people flying kites on a field. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2861", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000031738.jpg", "positive_caption": ["a pitcher on a mound, in motion, the ball in the air. is this a professional game? yes."], "negative_caption": ["a pitcher on a mound, in motion, the ball in the air. is this a professional game? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000332781.jpg", "positive_caption": ["a kite that looks like a grey kitty cat. is it a cloudy day? no."], "negative_caption": ["a kite that looks like a grey kitty cat. is it a cloudy day? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1779", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000578072.jpg", "positive_caption": ["a cat sitting on top of a chair. is this indoors? no."], "negative_caption": ["a cat sitting on top of a chair. is this indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4233", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000282456.jpg", "positive_caption": ["a couple sitting on a bench at the beach. is it daytime? yes."], "negative_caption": ["a couple sitting on a bench at the beach. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_702", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000188585.jpg", "positive_caption": ["a crowded baggage claim area of an airport. it this area well lit? yes."], "negative_caption": ["a crowded baggage claim area of an airport. it this area well lit? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2122", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000402264.jpg", "positive_caption": ["2 guys looking at their phones and another guy is wearing an orange hat. is this a construction site? no."], "negative_caption": ["2 guys looking at their phones and another guy is wearing an orange hat. is this a construction site? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5557", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000532983.jpg", "positive_caption": ["a large group of people sitting at tables. is this a meeting? no."], "negative_caption": ["a large group of people sitting at tables. is this a meeting? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10774", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000461404.jpg", "positive_caption": ["the men row the boat while the cows stand in the water. is this in a river? yes."], "negative_caption": ["the men row the boat while the cows stand in the water. is this in a river? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2185", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000231502.jpg", "positive_caption": ["2 people standing in front of 3 unpeeled bananas. are they holding the bananas? no."], "negative_caption": ["2 people standing in front of 3 unpeeled bananas. are they holding the bananas? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4889", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000218941.jpg", "positive_caption": ["a child is eating and has a messy face. is it light out? yes."], "negative_caption": ["a child is eating and has a messy face. is it light out? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5588", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000424544.jpg", "positive_caption": ["a man holding a baseball bat ready to hit the ball. is this a black and white picture? no."], "negative_caption": ["a man holding a baseball bat ready to hit the ball. is this a black and white picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1178", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000056504.jpg", "positive_caption": ["a group of people that are holding onto sheep. is this photo in color? yes."], "negative_caption": ["a group of people that are holding onto sheep. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9457", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000287239.jpg", "positive_caption": ["a mother brushing her child's hair with a plastic brush. is this a precious moment? yes."], "negative_caption": ["a mother brushing her child's hair with a plastic brush. is this a precious moment? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2900", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000246382.jpg", "positive_caption": ["a photo of a blender containing oranges, bananas and strawberries. it is color pic? yes."], "negative_caption": ["a photo of a blender containing oranges, bananas and strawberries. it is color pic? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1911", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000321495.jpg", "positive_caption": ["a woman is sitting in front of a news back drop. is she an anchor? yes."], "negative_caption": ["a woman is sitting in front of a news back drop. is she an anchor? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1807", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000406734.jpg", "positive_caption": ["crowds on the street walking around in town. is it a large crowd? yes."], "negative_caption": ["crowds on the street walking around in town. is it a large crowd? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7565", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000325629.jpg", "positive_caption": ["mass transmit coming down a coastal railroad track. is this a color image? yes."], "negative_caption": ["mass transmit coming down a coastal railroad track. is this a color image? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1218", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000114169.jpg", "positive_caption": ["the pizza has been prepared and sliced for serving. is it at home? no."], "negative_caption": ["the pizza has been prepared and sliced for serving. is it at home? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4527", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000461187.jpg", "positive_caption": ["a man in business attire speaks holds a cell phone near his ear. is this photo in color? yes."], "negative_caption": ["a man in business attire speaks holds a cell phone near his ear. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_918", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000446106.jpg", "positive_caption": ["a man in a suit and tie standing next to shirts and ties. is this a color picture? yes."], "negative_caption": ["a man in a suit and tie standing next to shirts and ties. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4149", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000042135.jpg", "positive_caption": ["the zebra in this shot separates the brown grass from the blue tone of the field and sky. is it a zoo? no."], "negative_caption": ["the zebra in this shot separates the brown grass from the blue tone of the field and sky. is it a zoo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9086", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000057672.jpg", "positive_caption": ["a rivera group of people with life jacket rowing a long boat in. is it a fishing boat? no."], "negative_caption": ["a rivera group of people with life jacket rowing a long boat in. is it a fishing boat? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10342", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000226053.jpg", "positive_caption": ["a great shot of a mountain near the ocean. is this photo in color? yes."], "negative_caption": ["a great shot of a mountain near the ocean. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3357", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000016283.jpg", "positive_caption": ["a series of 4 photos showing a group of people preparing food in a kitchen. is it just the 4 photos? yes."], "negative_caption": ["a series of 4 photos showing a group of people preparing food in a kitchen. is it just the 4 photos? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2947", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000174176.jpg", "positive_caption": ["man skate boarding on snow down the mountain. is it snowboard? yes."], "negative_caption": ["man skate boarding on snow down the mountain. is it snowboard? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1819", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000398567.jpg", "positive_caption": ["the computer is on a wooden computer desk. is it a laptop? no."], "negative_caption": ["the computer is on a wooden computer desk. is it a laptop? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9263", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000099030.jpg", "positive_caption": ["a clean and fully furnished modern looking kitchen. does it look like home kitchen? yes."], "negative_caption": ["a clean and fully furnished modern looking kitchen. does it look like home kitchen? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6434", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000074067.jpg", "positive_caption": ["a man extending a racquet toward a tennis ball. is this a black and white photo? no."], "negative_caption": ["a man extending a racquet toward a tennis ball. is this a black and white photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10720", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000383211.jpg", "positive_caption": ["a woman is taking a picture of herself in a mirror. is she blonde? no."], "negative_caption": ["a woman is taking a picture of herself in a mirror. is she blonde? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9069", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000361763.jpg", "positive_caption": ["interesting antics by 2 men during a baseball game. are these men spectators? no."], "negative_caption": ["interesting antics by 2 men during a baseball game. are these men spectators? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7802", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000220118.jpg", "positive_caption": ["a dog sitting on a rock area at water's edge of a lake. does this look like a professional shot? no."], "negative_caption": ["a dog sitting on a rock area at water's edge of a lake. does this look like a professional shot? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8922", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000305451.jpg", "positive_caption": ["a father and daughter placing cheese on a home made pizza. are they at a restaurant? no."], "negative_caption": ["a father and daughter placing cheese on a home made pizza. are they at a restaurant? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6355", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000221307.jpg", "positive_caption": ["modern bathroom with exotic tiling and counter top. is this photo in color? yes."], "negative_caption": ["modern bathroom with exotic tiling and counter top. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9583", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000163707.jpg", "positive_caption": ["an unoccupied bench along a path by the water. is it old? yes."], "negative_caption": ["an unoccupied bench along a path by the water. is it old? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4220", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000147173.jpg", "positive_caption": ["a group of skateboarders sitting outside on some concrete. are they at a skate park? no."], "negative_caption": ["a group of skateboarders sitting outside on some concrete. are they at a skate park? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9948", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000168619.jpg", "positive_caption": ["a paved path stretches through the grass under the cloudy sky. is this a dirt path? no."], "negative_caption": ["a paved path stretches through the grass under the cloudy sky. is this a dirt path? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10258", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000393634.jpg", "positive_caption": ["an orange colorful umbrella is being held by a woman. is it raining? no."], "negative_caption": ["an orange colorful umbrella is being held by a woman. is it raining? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5639", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000426758.jpg", "positive_caption": ["a stop sign on a 1 way street. is it daytime? yes."], "negative_caption": ["a stop sign on a 1 way street. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_826", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000327820.jpg", "positive_caption": ["a crowd of people wearing ski wear and holding skis on a snow covered bank. is it snowing? no."], "negative_caption": ["a crowd of people wearing ski wear and holding skis on a snow covered bank. is it snowing? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5103", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000309413.jpg", "positive_caption": ["a man that with a baseball bat standing in the dirt. is this at a game? yes."], "negative_caption": ["a man that with a baseball bat standing in the dirt. is this at a game? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2501", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000030418.jpg", "positive_caption": ["2 trains parked next to each other on train tracks. are they at a train station? yes."], "negative_caption": ["2 trains parked next to each other on train tracks. are they at a train station? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3399", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000549201.jpg", "positive_caption": ["a person that is sitting down on a table. are they on top of the table? no."], "negative_caption": ["a person that is sitting down on a table. are they on top of the table? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_563", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000184822.jpg", "positive_caption": ["a bus riding on a street near an intersection. is it a school bus? no."], "negative_caption": ["a bus riding on a street near an intersection. is it a school bus? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4033", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000442143.jpg", "positive_caption": ["some giraffes are standing in the open ground. is this a zoo? yes."], "negative_caption": ["some giraffes are standing in the open ground. is this a zoo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9604", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000261115.jpg", "positive_caption": ["a view of a single bathtub in an otherwise empty bathroom. doe's this bathroom have windows? yes."], "negative_caption": ["a view of a single bathtub in an otherwise empty bathroom. doe's this bathroom have windows? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10729", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000489257.jpg", "positive_caption": ["a cat sits and stares while on a window sill. is he alone? yes."], "negative_caption": ["a cat sits and stares while on a window sill. is he alone? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8282", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000550844.jpg", "positive_caption": ["a bowl of cereal and fruits sit on the table. are there people in this photo? no."], "negative_caption": ["a bowl of cereal and fruits sit on the table. are there people in this photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3852", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000037863.jpg", "positive_caption": ["a dining area with umbrellas and lighting at night. is this outside? yes."], "negative_caption": ["a dining area with umbrellas and lighting at night. is this outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1482", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000393724.jpg", "positive_caption": ["a man wearing an orange ribbon is standing in a parking lot. is this daytime? yes."], "negative_caption": ["a man wearing an orange ribbon is standing in a parking lot. is this daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1595", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000114316.jpg", "positive_caption": ["a woman is working in a small kitchen. does she appear to be cooking? yes."], "negative_caption": ["a woman is working in a small kitchen. does she appear to be cooking? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5660", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000455853.jpg", "positive_caption": ["an person relishing it on a good daytime. is this picture in color? yes."], "negative_caption": ["an person relishing it on a good daytime. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4562", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000185303.jpg", "positive_caption": ["a picture of a woman laying on the purple sheets of a bed. is she sleeping? no."], "negative_caption": ["a picture of a woman laying on the purple sheets of a bed. is she sleeping? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8570", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000549042.jpg", "positive_caption": ["an elephant standing on top of a dirt and grass field. is this an adult elephant? yes."], "negative_caption": ["an elephant standing on top of a dirt and grass field. is this an adult elephant? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7038", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000476298.jpg", "positive_caption": ["a young fellow with black glasses is biting his box. is this indoors? yes."], "negative_caption": ["a young fellow with black glasses is biting his box. is this indoors? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9160", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000144436.jpg", "positive_caption": ["a woman is cooking tofu and vegetables in a kitchen. is it restaurant? no."], "negative_caption": ["a woman is cooking tofu and vegetables in a kitchen. is it restaurant? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2588", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000191625.jpg", "positive_caption": ["snowboarders are gliding down a mountain during the day. is this a color photo? yes."], "negative_caption": ["snowboarders are gliding down a mountain during the day. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3229", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000575610.jpg", "positive_caption": ["a crowd of people walking across a cross walk. is it a large crowd? yes."], "negative_caption": ["a crowd of people walking across a cross walk. is it a large crowd? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9524", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000577160.jpg", "positive_caption": ["a sandwich with various toppings next to a sweet potato. is this image in color? yes."], "negative_caption": ["a sandwich with various toppings next to a sweet potato. is this image in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8553", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000009465.jpg", "positive_caption": ["a vintage image of a very nice looking horse drawn carriage. is it inside? no."], "negative_caption": ["a vintage image of a very nice looking horse drawn carriage. is it inside? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3794", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000402364.jpg", "positive_caption": ["a computer monitor expressing disappointment on the screen with mouse. is it laptop? no."], "negative_caption": ["a computer monitor expressing disappointment on the screen with mouse. is it laptop? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4024", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000116944.jpg", "positive_caption": ["a stove and sink in a small kitchen. is this a black and white picture? no."], "negative_caption": ["a stove and sink in a small kitchen. is this a black and white picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2403", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000229142.jpg", "positive_caption": ["a kitchen with an oven and refrigerator. does this kitchen look neat and clean? yes."], "negative_caption": ["a kitchen with an oven and refrigerator. does this kitchen look neat and clean? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1434", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000438304.jpg", "positive_caption": ["an advertisement for tennis gear with 2 players in tennis stances. is this on a billboard? no."], "negative_caption": ["an advertisement for tennis gear with 2 players in tennis stances. is this on a billboard? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8046", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000346360.jpg", "positive_caption": ["2 men standing in a living room by a couch playing wii. can you see the game that is being played? no."], "negative_caption": ["2 men standing in a living room by a couch playing wii. can you see the game that is being played? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5191", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000470207.jpg", "positive_caption": ["a rider on a motorcycle racing on track. is it dark? no."], "negative_caption": ["a rider on a motorcycle racing on track. is it dark? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3571", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000079453.jpg", "positive_caption": ["multiple colorful ties displayed on a pipe rack. are they men's neck ties? yes."], "negative_caption": ["multiple colorful ties displayed on a pipe rack. are they men's neck ties? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2748", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000030585.jpg", "positive_caption": ["an orangee truck is waiting to come through the gate. is it large truck? yes."], "negative_caption": ["an orangee truck is waiting to come through the gate. is it large truck? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5468", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000575349.jpg", "positive_caption": ["young child wearing a fireman's hat eating food. is this a boy? yes."], "negative_caption": ["young child wearing a fireman's hat eating food. is this a boy? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9673", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000074517.jpg", "positive_caption": ["a small living with a laptop, couch, and smaller television. is this a small living room? yes."], "negative_caption": ["a small living with a laptop, couch, and smaller television. is this a small living room? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4996", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000355674.jpg", "positive_caption": ["a bunch of people are standing out on a beach. does it look like there is an event going on? no."], "negative_caption": ["a bunch of people are standing out on a beach. does it look like there is an event going on? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5324", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000274035.jpg", "positive_caption": ["a man at a spectator tennis game running to hit the tennis ball. is this man 1 of the player? yes."], "negative_caption": ["a man at a spectator tennis game running to hit the tennis ball. is this man 1 of the player? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_11093", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000052270.jpg", "positive_caption": ["a table at a restaurant with 2 plates and a cup of coffee. is this picture in color? yes."], "negative_caption": ["a table at a restaurant with 2 plates and a cup of coffee. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4098", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000160596.jpg", "positive_caption": ["a person in orange jacket sitting at 2 park benches with green grass in the background. is the person sitting on both benches? no."], "negative_caption": ["a person in orange jacket sitting at 2 park benches with green grass in the background. is the person sitting on both benches? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1119", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000003751.jpg", "positive_caption": ["there are many suitcases, shoes and bags on the floor. is this indoors? yes."], "negative_caption": ["there are many suitcases, shoes and bags on the floor. is this indoors? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5606", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000398941.jpg", "positive_caption": ["a indigenous woman walking alone with an umbrella. is it raining? no."], "negative_caption": ["a indigenous woman walking alone with an umbrella. is it raining? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1682", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000455370.jpg", "positive_caption": ["a group of people and an ox-drawn carriage on dirt road. are they putting on a show? no."], "negative_caption": ["a group of people and an ox-drawn carriage on dirt road. are they putting on a show? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5263", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000243580.jpg", "positive_caption": ["a kitchen filled with appliances and wooden cabinets. is this all stainless steel? no."], "negative_caption": ["a kitchen filled with appliances and wooden cabinets. is this all stainless steel? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3773", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000543337.jpg", "positive_caption": ["the batter is swinging his bat in the game. is this pro game? yes."], "negative_caption": ["the batter is swinging his bat in the game. is this pro game? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1259", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000032609.jpg", "positive_caption": ["an old photograph depicts a young boy in nice clothes. is it a color photo? no."], "negative_caption": ["an old photograph depicts a young boy in nice clothes. is it a color photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10434", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000097213.jpg", "positive_caption": ["a city with cars coming down the street. are they in the city? yes."], "negative_caption": ["a city with cars coming down the street. are they in the city? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3381", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000473029.jpg", "positive_caption": ["2 people stand at a sink in a commercial kitchen. are they stand at the bathroom sink? no."], "negative_caption": ["2 people stand at a sink in a commercial kitchen. are they stand at the bathroom sink? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5467", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000167683.jpg", "positive_caption": ["there is a woman that is making sandwiches at a deli. is she wearing an apron? yes."], "negative_caption": ["there is a woman that is making sandwiches at a deli. is she wearing an apron? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2356", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000120176.jpg", "positive_caption": ["a chicken burger with mushrooms and tomatoes. are there fries with it? no."], "negative_caption": ["a chicken burger with mushrooms and tomatoes. are there fries with it? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_985", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000370802.jpg", "positive_caption": ["there are 3 men that are sitting at a table together. are they older men? yes."], "negative_caption": ["there are 3 men that are sitting at a table together. are they older men? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1242", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000460392.jpg", "positive_caption": ["a woman on skis on the ski slopes. is it snowing? no."], "negative_caption": ["a woman on skis on the ski slopes. is it snowing? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5579", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000251988.jpg", "positive_caption": ["a white plate topped with different types of foods. does the plate have any decoration on it? no."], "negative_caption": ["a white plate topped with different types of foods. does the plate have any decoration on it? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1437", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000497261.jpg", "positive_caption": ["a batter, catcher and umpire in a baseball game. is this picture in color? yes."], "negative_caption": ["a batter, catcher and umpire in a baseball game. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3625", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000351463.jpg", "positive_caption": ["a man that is carrying a baseball bat. is this color? yes."], "negative_caption": ["a man that is carrying a baseball bat. is this color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9007", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000066255.jpg", "positive_caption": ["an airplane banks into a left turn in a cloudy sky. is it just taking off? no."], "negative_caption": ["an airplane banks into a left turn in a cloudy sky. is it just taking off? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2528", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000554625.jpg", "positive_caption": ["a small child wearing headphones plays on the computer. is this in a home office? no."], "negative_caption": ["a small child wearing headphones plays on the computer. is this in a home office? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8048", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000052502.jpg", "positive_caption": ["a fork and a pizza on a table. is it a whole pizza? yes."], "negative_caption": ["a fork and a pizza on a table. is it a whole pizza? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3369", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000410320.jpg", "positive_caption": ["2 subway trains that are red, yellow and blue. is this in a tunnel? no."], "negative_caption": ["2 subway trains that are red, yellow and blue. is this in a tunnel? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1514", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000421333.jpg", "positive_caption": ["a big black dog trying to carry a large tree limb. is it a lab? no."], "negative_caption": ["a big black dog trying to carry a large tree limb. is it a lab? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3018", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000003770.jpg", "positive_caption": ["a girl playing tennis while hitting a serve. is this a color picture? yes."], "negative_caption": ["a girl playing tennis while hitting a serve. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2558", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000474759.jpg", "positive_caption": ["a cake that has a bunch of angry birds on it. is it a birthday cake? yes."], "negative_caption": ["a cake that has a bunch of angry birds on it. is it a birthday cake? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2507", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000531289.jpg", "positive_caption": ["a cake on a plate has just been sliced. are there people in this photo? no."], "negative_caption": ["a cake on a plate has just been sliced. are there people in this photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5179", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000550979.jpg", "positive_caption": ["the giant elephant and giraffe is on display inside. is this in front of a zoo? no."], "negative_caption": ["the giant elephant and giraffe is on display inside. is this in front of a zoo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4201", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000395324.jpg", "positive_caption": ["a blue motorcycle is standing out in the open. is it police bike? no."], "negative_caption": ["a blue motorcycle is standing out in the open. is it police bike? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10470", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000340096.jpg", "positive_caption": ["a stop sign covered in lights at a street intersection. is it raining? no."], "negative_caption": ["a stop sign covered in lights at a street intersection. is it raining? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6295", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000291941.jpg", "positive_caption": ["a television burried in the sand on a beach. is this a flat screen? no."], "negative_caption": ["a television burried in the sand on a beach. is this a flat screen? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8936", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000380750.jpg", "positive_caption": ["a man in black wetsuit windsurfing on water. is he alone? yes."], "negative_caption": ["a man in black wetsuit windsurfing on water. is he alone? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6186", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000374725.jpg", "positive_caption": ["hundreds of sail boats docked in the water. is it look like ocean? yes."], "negative_caption": ["hundreds of sail boats docked in the water. is it look like ocean? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4707", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000486628.jpg", "positive_caption": ["a few kids in a street alley eating. is this picture in color? yes."], "negative_caption": ["a few kids in a street alley eating. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1717", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000470718.jpg", "positive_caption": ["a brown teddy bear is wearing a red and white suit. is someone holding it? no."], "negative_caption": ["a brown teddy bear is wearing a red and white suit. is someone holding it? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2416", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000529887.jpg", "positive_caption": ["a small white bird walking across a lush green field. is it day time? yes."], "negative_caption": ["a small white bird walking across a lush green field. is it day time? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3522", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000271586.jpg", "positive_caption": ["a jet airplane flying high in the sky. is this a color photo? yes."], "negative_caption": ["a jet airplane flying high in the sky. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4442", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000049119.jpg", "positive_caption": ["a motorcycle is parked in front of a body of water. is this a color image? yes."], "negative_caption": ["a motorcycle is parked in front of a body of water. is this a color image? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9085", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000402730.jpg", "positive_caption": ["a person with a cow in an arena. is this a man? yes."], "negative_caption": ["a person with a cow in an arena. is this a man? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4624", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000561468.jpg", "positive_caption": ["a bear that is standing in the street. is it real? yes."], "negative_caption": ["a bear that is standing in the street. is it real? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4656", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000122207.jpg", "positive_caption": ["a train engine carrying many carts past a traffic light on a track. is this train on the ground level? yes."], "negative_caption": ["a train engine carrying many carts past a traffic light on a track. is this train on the ground level? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_171", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000533291.jpg", "positive_caption": ["there is a snowboarder riding a jump into the air. is he wearing a mask? no."], "negative_caption": ["there is a snowboarder riding a jump into the air. is he wearing a mask? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6882", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000206385.jpg", "positive_caption": ["2 giraffes some rocks and trees 1 is laying down. are they adult giraffes? yes."], "negative_caption": ["2 giraffes some rocks and trees 1 is laying down. are they adult giraffes? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4640", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000543645.jpg", "positive_caption": ["2 people sitting at a outdoor table with drinks. are they in the backyard? no."], "negative_caption": ["2 people sitting at a outdoor table with drinks. are they in the backyard? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_350", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000154613.jpg", "positive_caption": ["desk in nice living room with fireplace and pictures. is this room living room? yes."], "negative_caption": ["desk in nice living room with fireplace and pictures. is this room living room? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3098", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000041688.jpg", "positive_caption": ["groups of bananas rest on the table with pineapples behind them. is this picture in color? yes."], "negative_caption": ["groups of bananas rest on the table with pineapples behind them. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1733", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000321092.jpg", "positive_caption": ["a grizzly bear lounges peacefully on the rocks. is this a color picture? yes."], "negative_caption": ["a grizzly bear lounges peacefully on the rocks. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_750", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000228329.jpg", "positive_caption": ["a young man and young woman cut into a cake together. are they at a wedding? yes."], "negative_caption": ["a young man and young woman cut into a cake together. are they at a wedding? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_483", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000129339.jpg", "positive_caption": ["a cat that is sitting on some shoes. is this a color photo? yes."], "negative_caption": ["a cat that is sitting on some shoes. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9233", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000557855.jpg", "positive_caption": ["the baseball equipment was left in the grass. is it a bat? no."], "negative_caption": ["the baseball equipment was left in the grass. is it a bat? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3417", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000359323.jpg", "positive_caption": ["2 elephants stand side by side in a grassy open area with a tree in the background. does this look like a zoo? no."], "negative_caption": ["2 elephants stand side by side in a grassy open area with a tree in the background. does this look like a zoo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5447", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000337833.jpg", "positive_caption": ["a young boy standing in front of a giraffe. is it a color image? yes."], "negative_caption": ["a young boy standing in front of a giraffe. is it a color image? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2973", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000013333.jpg", "positive_caption": ["a stop sign sits near a field and a mountain. is it currently snowing? no."], "negative_caption": ["a stop sign sits near a field and a mountain. is it currently snowing? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8731", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000516500.jpg", "positive_caption": ["a boy on a skateboard is on a gray sidewalk near a building. is this photo in color? yes."], "negative_caption": ["a boy on a skateboard is on a gray sidewalk near a building. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_576", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000494014.jpg", "positive_caption": ["this looks like a mcdonald's in a chinese or japanese community. is this picture taken in color? yes."], "negative_caption": ["this looks like a mcdonald's in a chinese or japanese community. is this picture taken in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7569", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000556620.jpg", "positive_caption": ["a black and white photo of 3 people holding surf boards near a shoreline. are there any women in this photo? no."], "negative_caption": ["a black and white photo of 3 people holding surf boards near a shoreline. are there any women in this photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5212", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000492402.jpg", "positive_caption": ["a couple of women playing a game with remote controllers. is this a color photo? yes."], "negative_caption": ["a couple of women playing a game with remote controllers. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1990", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000566538.jpg", "positive_caption": ["an elephant standing on top of a dirt field. is this in daytime? yes."], "negative_caption": ["an elephant standing on top of a dirt field. is this in daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8196", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000041588.jpg", "positive_caption": ["some airplanes are on the tarmac with a truck. is it daytime? yes."], "negative_caption": ["some airplanes are on the tarmac with a truck. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3839", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000039971.jpg", "positive_caption": ["the side view train carts on top of rail road tracks. is this picture in color? yes."], "negative_caption": ["the side view train carts on top of rail road tracks. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3068", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000081017.jpg", "positive_caption": ["the living room is clean and empty of people. is this a color photo? yes."], "negative_caption": ["the living room is clean and empty of people. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1372", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000364444.jpg", "positive_caption": ["a room with several televisions inside showing sports. is this room crowded with people? no."], "negative_caption": ["a room with several televisions inside showing sports. is this room crowded with people? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10212", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000052609.jpg", "positive_caption": ["this red and black truck maybe on display. is this truck on concrete? no."], "negative_caption": ["this red and black truck maybe on display. is this truck on concrete? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1742", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000250993.jpg", "positive_caption": ["there are plenty of doughnuts on the table. are they in a box? no."], "negative_caption": ["there are plenty of doughnuts on the table. are they in a box? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7150", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000235836.jpg", "positive_caption": ["a child playing with a plastic bat and ball in a yard next to a garage. is it a color image? yes."], "negative_caption": ["a child playing with a plastic bat and ball in a yard next to a garage. is it a color image? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8394", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000321410.jpg", "positive_caption": ["3 people holding a surf board on a walk way. are they at a beach? no."], "negative_caption": ["3 people holding a surf board on a walk way. are they at a beach? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2050", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000202653.jpg", "positive_caption": ["a romantic couple sits close together on a park bench. is it night time? no."], "negative_caption": ["a romantic couple sits close together on a park bench. is it night time? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9438", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000313968.jpg", "positive_caption": ["a lady with a white cat on her shoulder. is she wearing a hat? no."], "negative_caption": ["a lady with a white cat on her shoulder. is she wearing a hat? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3484", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000346716.jpg", "positive_caption": ["double decker buses in progress down a crowded street. is this urban setting? yes."], "negative_caption": ["double decker buses in progress down a crowded street. is this urban setting? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10414", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000024958.jpg", "positive_caption": ["the man wearing glasses is talking on the cell phone. are they sunglasses? no."], "negative_caption": ["the man wearing glasses is talking on the cell phone. are they sunglasses? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9888", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000104696.jpg", "positive_caption": ["a red clock tower on an old british city street. is it close up? no."], "negative_caption": ["a red clock tower on an old british city street. is it close up? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3984", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000431364.jpg", "positive_caption": ["a woman carrying an umbrella walking down a foot path. is it raining? yes."], "negative_caption": ["a woman carrying an umbrella walking down a foot path. is it raining? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8715", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000471154.jpg", "positive_caption": ["2 people sit on a golf cart, the man is on the phone. is both of them men? no."], "negative_caption": ["2 people sit on a golf cart, the man is on the phone. is both of them men? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10428", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000537066.jpg", "positive_caption": ["many boats are sitting near the shore outside a city. can you tell what city it is? no."], "negative_caption": ["many boats are sitting near the shore outside a city. can you tell what city it is? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4563", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000348481.jpg", "positive_caption": ["a laptop, phone, keys and other accessories sitting on a table. is this photo in color? yes."], "negative_caption": ["a laptop, phone, keys and other accessories sitting on a table. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10821", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000536934.jpg", "positive_caption": ["a gray tabby cat sleeping with its head on a laptop computer. is this close up? yes."], "negative_caption": ["a gray tabby cat sleeping with its head on a laptop computer. is this close up? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2726", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000313434.jpg", "positive_caption": ["many people are at their respected tables. are they outdoors? no."], "negative_caption": ["many people are at their respected tables. are they outdoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3388", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000498091.jpg", "positive_caption": ["a dog and 2 swans sitting on a hotel bed. is this a color picture? yes."], "negative_caption": ["a dog and 2 swans sitting on a hotel bed. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6800", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000256286.jpg", "positive_caption": ["a smokey gray kitty plays with a shoestring. is this a color photo? yes."], "negative_caption": ["a smokey gray kitty plays with a shoestring. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5511", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000146973.jpg", "positive_caption": ["a close up a plate filled with a variety of chocolate desserts. is this a restaurant scene? yes."], "negative_caption": ["a close up a plate filled with a variety of chocolate desserts. is this a restaurant scene? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10490", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000504586.jpg", "positive_caption": ["a set of 3 beds sitting inside of a bedroom. are these bunks beds? no."], "negative_caption": ["a set of 3 beds sitting inside of a bedroom. are these bunks beds? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8456", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000526197.jpg", "positive_caption": ["donuts on display behind a glass with its name by the donut. is this photo in color? yes."], "negative_caption": ["donuts on display behind a glass with its name by the donut. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10397", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000447728.jpg", "positive_caption": ["a guy jumping from a snow covered hill on a snowboard. is it sunny out? yes."], "negative_caption": ["a guy jumping from a snow covered hill on a snowboard. is it sunny out? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4798", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000369866.jpg", "positive_caption": ["a woman with a pink umbrella watches motorcycle traffic under a city bypass. are they motorcycle police officers? no."], "negative_caption": ["a woman with a pink umbrella watches motorcycle traffic under a city bypass. are they motorcycle police officers? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1183", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000485317.jpg", "positive_caption": ["a living room area that has a desk with a desktop computer, and a television in the corner of the room. is it big tv? yes."], "negative_caption": ["a living room area that has a desk with a desktop computer, and a television in the corner of the room. is it big tv? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2687", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000008405.jpg", "positive_caption": ["yellow sunflowers are in a blue and white giraffe styled vase. is it inside? yes."], "negative_caption": ["yellow sunflowers are in a blue and white giraffe styled vase. is it inside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1451", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000274574.jpg", "positive_caption": ["a car is parked on the curb by the fire hydrant. ok, is this a city street? yes."], "negative_caption": ["a car is parked on the curb by the fire hydrant. ok, is this a city street? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5186", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000325758.jpg", "positive_caption": ["a kitchen is shown with a sink and refrigerator. is this bedroom? no."], "negative_caption": ["a kitchen is shown with a sink and refrigerator. is this bedroom? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2769", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000037011.jpg", "positive_caption": ["a big bull standing out in a field alone. does it have horns? yes."], "negative_caption": ["a big bull standing out in a field alone. does it have horns? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5950", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000140450.jpg", "positive_caption": ["the guy wearing a scarf and microphone is holding his hand out for something. is this photo in color? yes."], "negative_caption": ["the guy wearing a scarf and microphone is holding his hand out for something. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5649", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000035210.jpg", "positive_caption": ["a muffin is adorned with a topping of nuts. is this photo in color? yes."], "negative_caption": ["a muffin is adorned with a topping of nuts. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7195", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000475839.jpg", "positive_caption": ["a skateboarder is performing a stunt high in the air. is it a boy? yes."], "negative_caption": ["a skateboarder is performing a stunt high in the air. is it a boy? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1117", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000035282.jpg", "positive_caption": ["a large sign on top of a gas station. it is city? yes."], "negative_caption": ["a large sign on top of a gas station. it is city? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9055", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000070791.jpg", "positive_caption": ["a surfer stands in knee high water in the ocean. is this a male? yes."], "negative_caption": ["a surfer stands in knee high water in the ocean. is this a male? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9204", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000144388.jpg", "positive_caption": ["some people sitting down on a bench and eating in front people. is it a park? no."], "negative_caption": ["some people sitting down on a bench and eating in front people. is it a park? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5357", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000298031.jpg", "positive_caption": ["a small group of skateboarders relaxing during a break from practice. do they have an audience around? no."], "negative_caption": ["a small group of skateboarders relaxing during a break from practice. do they have an audience around? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4509", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000130386.jpg", "positive_caption": ["a large blue sign is next to a building. does the sign have a white p on it? no."], "negative_caption": ["a large blue sign is next to a building. does the sign have a white p on it? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8762", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000173166.jpg", "positive_caption": ["2 giraffes stand next to each other by some trees. do you think that this is in a zoo? yes."], "negative_caption": ["2 giraffes stand next to each other by some trees. do you think that this is in a zoo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9561", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000109390.jpg", "positive_caption": ["a kitchen with white cabinets and stainless steel stove. is food being prepared right now in this photo? no."], "negative_caption": ["a kitchen with white cabinets and stainless steel stove. is food being prepared right now in this photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5550", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000464440.jpg", "positive_caption": ["a tall wooden clock tower towering above a city. is this clock very tall? yes."], "negative_caption": ["a tall wooden clock tower towering above a city. is this clock very tall? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_676", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000563024.jpg", "positive_caption": ["a lunch box with apples and cut sandwich pieces. is this picture in color? yes."], "negative_caption": ["a lunch box with apples and cut sandwich pieces. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4540", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000160531.jpg", "positive_caption": ["a young man pointing a remote at the tv. is this picture in color? no."], "negative_caption": ["a young man pointing a remote at the tv. is this picture in color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8920", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000525559.jpg", "positive_caption": ["a parent zebra stands next to a very young zebra. is it a newborn? no."], "negative_caption": ["a parent zebra stands next to a very young zebra. is it a newborn? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7254", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000225539.jpg", "positive_caption": ["a couple of people that are eating some food. is this couple a man and woman? yes."], "negative_caption": ["a couple of people that are eating some food. is this couple a man and woman? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3090", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000300479.jpg", "positive_caption": ["a locomotive parked on a display with steps coming out of it. is this in a building? no."], "negative_caption": ["a locomotive parked on a display with steps coming out of it. is this in a building? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8390", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000253308.jpg", "positive_caption": ["a brown and white owl and some green bushes. is this outside? yes."], "negative_caption": ["a brown and white owl and some green bushes. is this outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1965", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000076117.jpg", "positive_caption": ["an image from behind a windshield of an ordinary street. is it raining? no."], "negative_caption": ["an image from behind a windshield of an ordinary street. is it raining? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6012", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000255335.jpg", "positive_caption": ["a low shot of a medieval clock tower. are there any people in this picture? no."], "negative_caption": ["a low shot of a medieval clock tower. are there any people in this picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2090", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000158391.jpg", "positive_caption": ["a man in striped shorts surfing on a long surfboard with the tip of the board pointing upward against the waves. is this in the ocean? yes."], "negative_caption": ["a man in striped shorts surfing on a long surfboard with the tip of the board pointing upward against the waves. is this in the ocean? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3597", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000159127.jpg", "positive_caption": ["a black cat sitting on a desk with a computer. is it a laptop? no."], "negative_caption": ["a black cat sitting on a desk with a computer. is it a laptop? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_334", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000122108.jpg", "positive_caption": ["2 giraffes in front of a rocky mountain inside a wooden fence. is this at a zoo? yes."], "negative_caption": ["2 giraffes in front of a rocky mountain inside a wooden fence. is this at a zoo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2283", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000196653.jpg", "positive_caption": ["a person on a train holding a video game controller with other electronics around. is this person sitting? yes."], "negative_caption": ["a person on a train holding a video game controller with other electronics around. is this person sitting? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2641", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000295798.jpg", "positive_caption": ["a couple of soldiers riding on the back of brown horses. is this a color photo? yes."], "negative_caption": ["a couple of soldiers riding on the back of brown horses. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6970", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000114187.jpg", "positive_caption": ["a desk with a monitor a keyboard and a mouse. is it a wooden desk? yes."], "negative_caption": ["a desk with a monitor a keyboard and a mouse. is it a wooden desk? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10949", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000198841.jpg", "positive_caption": ["a small plant is sitting in a vase. is this a small vase? no."], "negative_caption": ["a small plant is sitting in a vase. is this a small vase? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8562", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000422395.jpg", "positive_caption": ["a very small bathroom with 2 toilet paper holders. is toilet paper on both rolls? no."], "negative_caption": ["a very small bathroom with 2 toilet paper holders. is toilet paper on both rolls? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3227", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000216954.jpg", "positive_caption": ["a kitchen with a long counter and a painting on the wall above. is this picture in color? yes."], "negative_caption": ["a kitchen with a long counter and a painting on the wall above. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5428", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000028998.jpg", "positive_caption": ["a small boy in a red shirt is holding a donut. is this inside? no."], "negative_caption": ["a small boy in a red shirt is holding a donut. is this inside? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8156", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000239888.jpg", "positive_caption": ["a bear walks alongside a road near a tree. is this a color picture? yes."], "negative_caption": ["a bear walks alongside a road near a tree. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10063", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000011129.jpg", "positive_caption": ["a female tennis player in a action on the court. is she young? yes."], "negative_caption": ["a female tennis player in a action on the court. is she young? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2568", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000519157.jpg", "positive_caption": ["he will buy a product in the refrigerator. is this in a store? yes."], "negative_caption": ["he will buy a product in the refrigerator. is this in a store? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6066", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000434092.jpg", "positive_caption": ["2 people standing next to each other against a wall. is this a color picture? yes."], "negative_caption": ["2 people standing next to each other against a wall. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4554", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000040423.jpg", "positive_caption": ["a man standing in the rain talking on a phone. is he using an umbrella? no."], "negative_caption": ["a man standing in the rain talking on a phone. is he using an umbrella? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2186", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000152158.jpg", "positive_caption": ["a man holding a bat at a baseball field. is it daytime? yes."], "negative_caption": ["a man holding a bat at a baseball field. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10071", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000409178.jpg", "positive_caption": ["a person riding skis down a snow covered slope. is it a color image? yes."], "negative_caption": ["a person riding skis down a snow covered slope. is it a color image? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7500", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000216852.jpg", "positive_caption": ["a woman sitting on the couch with her legs crossed. is she wearing a skirt? no."], "negative_caption": ["a woman sitting on the couch with her legs crossed. is she wearing a skirt? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10403", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000075754.jpg", "positive_caption": ["a woman displaying a gadget to the camera. is it in color? yes."], "negative_caption": ["a woman displaying a gadget to the camera. is it in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3331", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000186130.jpg", "positive_caption": ["a person cutting a cake with a knife. is it a birthday cake? no."], "negative_caption": ["a person cutting a cake with a knife. is it a birthday cake? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10006", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000541664.jpg", "positive_caption": ["a number of lego toys near a laptop. is this picture in color? yes."], "negative_caption": ["a number of lego toys near a laptop. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10269", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000115226.jpg", "positive_caption": ["an image of a person petting someone's dog outside in the rain. is this a painting? no."], "negative_caption": ["an image of a person petting someone's dog outside in the rain. is this a painting? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_800", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000225511.jpg", "positive_caption": ["a man walking a tight rope in a circus. is this outdoors? yes."], "negative_caption": ["a man walking a tight rope in a circus. is this outdoors? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4930", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000565570.jpg", "positive_caption": ["young man preparing to throw pitch from mound at baseball field. is it a stadium? no."], "negative_caption": ["young man preparing to throw pitch from mound at baseball field. is it a stadium? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7758", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000415570.jpg", "positive_caption": ["healthy well balanced meal with protein, dairy, vegetables and carbs. it is a photo of a chart? no."], "negative_caption": ["healthy well balanced meal with protein, dairy, vegetables and carbs. it is a photo of a chart? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_599", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000055879.jpg", "positive_caption": ["a old photo shows a man with his 2 horses. is this in black and white? yes."], "negative_caption": ["a old photo shows a man with his 2 horses. is this in black and white? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_127", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000118895.jpg", "positive_caption": ["3 cows standing beside a sidewalk that has people walking on it. is this a color photo? no."], "negative_caption": ["3 cows standing beside a sidewalk that has people walking on it. is this a color photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4576", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000095390.jpg", "positive_caption": ["a train bridge off in the distance with a train about to go over it. is it daytime? yes."], "negative_caption": ["a train bridge off in the distance with a train about to go over it. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1856", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000192862.jpg", "positive_caption": ["a little brown teddy bear hands from a door for somebody to take it. this description is a little odd, is someone handing the bear out the door? no."], "negative_caption": ["a little brown teddy bear hands from a door for somebody to take it. this description is a little odd, is someone handing the bear out the door? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4891", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000203631.jpg", "positive_caption": ["a young skier holding his skis posing for a picture. is this picture in color? yes."], "negative_caption": ["a young skier holding his skis posing for a picture. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8122", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000027298.jpg", "positive_caption": ["a commercial bathroom with a baby changing station. is this a color picture? yes."], "negative_caption": ["a commercial bathroom with a baby changing station. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5600", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000494240.jpg", "positive_caption": ["a group of elephants standing by the water with birds standing in the water. is it sunny outside? yes."], "negative_caption": ["a group of elephants standing by the water with birds standing in the water. is it sunny outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6035", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000100717.jpg", "positive_caption": ["en engaged woman sitting with her hands in her lap. is this image in color? yes."], "negative_caption": ["en engaged woman sitting with her hands in her lap. is this image in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3856", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000242885.jpg", "positive_caption": ["a refrigerator with doubles doors is sitting open. is it a stainless refrigerator? no."], "negative_caption": ["a refrigerator with doubles doors is sitting open. is it a stainless refrigerator? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7137", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000361939.jpg", "positive_caption": ["a group of people in a boat with a bicycle. is this photo in black and white? no."], "negative_caption": ["a group of people in a boat with a bicycle. is this photo in black and white? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1914", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000255494.jpg", "positive_caption": ["a black and white couple and a motorcycle. is it a modern picture? yes."], "negative_caption": ["a black and white couple and a motorcycle. is it a modern picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6180", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000492030.jpg", "positive_caption": ["a man and a dog playing in the ocean. is it day time? yes."], "negative_caption": ["a man and a dog playing in the ocean. is it day time? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4132", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000407159.jpg", "positive_caption": ["there are many girls on a field playing soccer. does it look like summertime? yes."], "negative_caption": ["there are many girls on a field playing soccer. does it look like summertime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_868", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000259690.jpg", "positive_caption": ["a man standing next to another person in a wheel chair. are these people outside? yes."], "negative_caption": ["a man standing next to another person in a wheel chair. are these people outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7589", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000581183.jpg", "positive_caption": ["a group of circus elephants standing on each others backs. do they headdresses on? yes."], "negative_caption": ["a group of circus elephants standing on each others backs. do they headdresses on? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10363", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000561894.jpg", "positive_caption": ["a fridge with magnets, a counter and a clock. is this in a home? yes."], "negative_caption": ["a fridge with magnets, a counter and a clock. is this in a home? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1066", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000458592.jpg", "positive_caption": ["a bathroom with yellow walls and marble counter. is this a modern bathroom? yes."], "negative_caption": ["a bathroom with yellow walls and marble counter. is this a modern bathroom? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4178", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000436918.jpg", "positive_caption": ["an overhead view looking into a beige colored toilet. is this picture in color? yes."], "negative_caption": ["an overhead view looking into a beige colored toilet. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5180", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000403677.jpg", "positive_caption": ["a women who is looking at her cell phone. is it a color photo? yes."], "negative_caption": ["a women who is looking at her cell phone. is it a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6754", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000168173.jpg", "positive_caption": ["a man is standing at a prep table making a sandwich. is he alone? yes."], "negative_caption": ["a man is standing at a prep table making a sandwich. is he alone? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_684", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000301121.jpg", "positive_caption": ["a woman sits on a bus, presumably waiting for a bench. are they reading advertisement? no."], "negative_caption": ["a woman sits on a bus, presumably waiting for a bench. are they reading advertisement? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3785", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000209222.jpg", "positive_caption": ["a man sitting on a bench in a park. is this a color picture? no."], "negative_caption": ["a man sitting on a bench in a park. is this a color picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7838", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000190406.jpg", "positive_caption": ["a double decker trolley car moving along a city street. is this picture in color? no."], "negative_caption": ["a double decker trolley car moving along a city street. is this picture in color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9990", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000552463.jpg", "positive_caption": ["a man who is holding a tennis racket. is he wearing a sun visor? no."], "negative_caption": ["a man who is holding a tennis racket. is he wearing a sun visor? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6767", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000548780.jpg", "positive_caption": ["2 people sit on a bench with pigeons and other people nearby. is this a park? yes."], "negative_caption": ["2 people sit on a bench with pigeons and other people nearby. is this a park? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8865", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000297544.jpg", "positive_caption": ["a man and a boy riding a motorbike behind a pickup truck loaded with pineapples. are either of them wearing helmets? no."], "negative_caption": ["a man and a boy riding a motorbike behind a pickup truck loaded with pineapples. are either of them wearing helmets? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1630", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000078106.jpg", "positive_caption": ["a bird has it's wings wide open as it flies downward toward a park. is it a crow? no."], "negative_caption": ["a bird has it's wings wide open as it flies downward toward a park. is it a crow? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2668", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000355677.jpg", "positive_caption": ["a lifeguard post is empty next to water. is this a swimming pool? no."], "negative_caption": ["a lifeguard post is empty next to water. is this a swimming pool? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10164", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000237193.jpg", "positive_caption": ["a man and woman pose with a dog under a makeshift tent. is this a color photo? yes."], "negative_caption": ["a man and woman pose with a dog under a makeshift tent. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3428", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000301156.jpg", "positive_caption": ["worker in white hard hat approaching the back of a white truck. is this in a city street? yes."], "negative_caption": ["worker in white hard hat approaching the back of a white truck. is this in a city street? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2879", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000226595.jpg", "positive_caption": ["a pizza with toppings including fresh greens sits ready to cut and eat. is this a large pizza? yes."], "negative_caption": ["a pizza with toppings including fresh greens sits ready to cut and eat. is this a large pizza? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3481", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000318146.jpg", "positive_caption": ["a person petting a horse that has a blonde mane. is this watermarked? no."], "negative_caption": ["a person petting a horse that has a blonde mane. is this watermarked? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9454", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000175151.jpg", "positive_caption": ["there is a bus moving down a street. is this a close up? no."], "negative_caption": ["there is a bus moving down a street. is this a close up? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10748", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000229184.jpg", "positive_caption": ["a lifeguard sits under an umbrella and looks out. is he alone? yes."], "negative_caption": ["a lifeguard sits under an umbrella and looks out. is he alone? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10793", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000235012.jpg", "positive_caption": ["some elephants and a man are in murky water. is this daytime? yes."], "negative_caption": ["some elephants and a man are in murky water. is this daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6383", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000161603.jpg", "positive_caption": ["a large cow walking around a stone room with 2 entrances. is this daytime? yes."], "negative_caption": ["a large cow walking around a stone room with 2 entrances. is this daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8604", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000221494.jpg", "positive_caption": ["the group of people are gathered together outside some have their umbrellas up. is this on a sidewalk? no."], "negative_caption": ["the group of people are gathered together outside some have their umbrellas up. is this on a sidewalk? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4525", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000262529.jpg", "positive_caption": ["a man reaching downward to strike a tennis ball. is this outside? yes."], "negative_caption": ["a man reaching downward to strike a tennis ball. is this outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5506", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000499202.jpg", "positive_caption": ["a elephant in the middle of a room. is this in a zoo? no."], "negative_caption": ["a elephant in the middle of a room. is this in a zoo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1532", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000407625.jpg", "positive_caption": ["a man in a suit and tie looks off to the side. does he have tie? yes."], "negative_caption": ["a man in a suit and tie looks off to the side. does he have tie? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4744", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000178812.jpg", "positive_caption": ["a pepperoni pizza sitting on a wooden table. is this a color picture? yes."], "negative_caption": ["a pepperoni pizza sitting on a wooden table. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6228", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000369644.jpg", "positive_caption": ["a row of 3 wall mounted urinals with a woman peeking behind a tree. is this a man's bathroom? yes."], "negative_caption": ["a row of 3 wall mounted urinals with a woman peeking behind a tree. is this a man's bathroom? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4552", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000045176.jpg", "positive_caption": ["a pug dog is looking away from its image in the mirror. is this a color image? yes."], "negative_caption": ["a pug dog is looking away from its image in the mirror. is this a color image? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_11037", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000022423.jpg", "positive_caption": ["an elephant removing the hat off of a man's head. is it sunny outside? yes."], "negative_caption": ["an elephant removing the hat off of a man's head. is it sunny outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10271", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000573659.jpg", "positive_caption": ["a computer on a very small table in an office. this computer is a laptop? no."], "negative_caption": ["a computer on a very small table in an office. this computer is a laptop? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4585", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000338132.jpg", "positive_caption": ["view from below of a church and the clock tower. is it rainy outside? no."], "negative_caption": ["view from below of a church and the clock tower. is it rainy outside? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5714", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000039670.jpg", "positive_caption": ["a train moving along a railway line in the bush. is it an older train? no."], "negative_caption": ["a train moving along a railway line in the bush. is it an older train? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10242", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000533402.jpg", "positive_caption": ["this is an image of a stature of babe ruth. is it outside? no."], "negative_caption": ["this is an image of a stature of babe ruth. is it outside? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2561", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000563404.jpg", "positive_caption": ["a bath room with a sink a mirror and a bath tub. so this is bathroom right? yes."], "negative_caption": ["a bath room with a sink a mirror and a bath tub. so this is bathroom right? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6457", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000052035.jpg", "positive_caption": ["an hawaiian jet airplane sitting on the runway of an airport. is it a big jet? yes."], "negative_caption": ["an hawaiian jet airplane sitting on the runway of an airport. is it a big jet? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6730", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000153267.jpg", "positive_caption": ["a beach and ocean with 3 kit boarders riding the waves and onlookers on the sand. is it sunny outside? yes."], "negative_caption": ["a beach and ocean with 3 kit boarders riding the waves and onlookers on the sand. is it sunny outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6917", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000396303.jpg", "positive_caption": ["people sitting outside of a cafe during the day. it is color picture? yes."], "negative_caption": ["people sitting outside of a cafe during the day. it is color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4464", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000137849.jpg", "positive_caption": ["young boy looking at elephants in conclusion the zoo. is this picture in color? yes."], "negative_caption": ["young boy looking at elephants in conclusion the zoo. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_72", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000162768.jpg", "positive_caption": ["5 signs giving directions to different places in the same direction. is this city? yes."], "negative_caption": ["5 signs giving directions to different places in the same direction. is this city? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2212", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000359147.jpg", "positive_caption": ["a boy skateboarding in a bowl at a skate park. is this picture in color? yes."], "negative_caption": ["a boy skateboarding in a bowl at a skate park. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_736", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000353017.jpg", "positive_caption": ["people walking the crosswalk pass a car on the street. is it crowded? no."], "negative_caption": ["people walking the crosswalk pass a car on the street. is it crowded? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4035", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000325102.jpg", "positive_caption": ["a man sitting on a couch with a plate of food. is the man holding the plate on his lap? no."], "negative_caption": ["a man sitting on a couch with a plate of food. is the man holding the plate on his lap? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10406", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000557965.jpg", "positive_caption": ["2 people riding on the backs of brown horses. are the people both female? no."], "negative_caption": ["2 people riding on the backs of brown horses. are the people both female? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7632", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000216277.jpg", "positive_caption": ["a partially eaten apple by a verizon device. is this a device eating an apple? no."], "negative_caption": ["a partially eaten apple by a verizon device. is this a device eating an apple? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10622", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000236332.jpg", "positive_caption": ["a stop sign in chinese is across the street from a large movie. is it an outdoor movie screen? no."], "negative_caption": ["a stop sign in chinese is across the street from a large movie. is it an outdoor movie screen? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4119", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000196865.jpg", "positive_caption": ["a pillow a bed a table and 2 books. is this black and white? no."], "negative_caption": ["a pillow a bed a table and 2 books. is this black and white? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8792", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000100603.jpg", "positive_caption": ["a person on horseback begins the trek down a large hill. is there more than 1 person in this photo? no."], "negative_caption": ["a person on horseback begins the trek down a large hill. is there more than 1 person in this photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1643", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000120188.jpg", "positive_caption": ["a woman holding a tennis racket drops a tennis ball. is she on a court? yes."], "negative_caption": ["a woman holding a tennis racket drops a tennis ball. is she on a court? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4881", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000277710.jpg", "positive_caption": ["a skier wearing a red, white and blue ski suit skis down a mountain. is this picture in color? yes."], "negative_caption": ["a skier wearing a red, white and blue ski suit skis down a mountain. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9587", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000364221.jpg", "positive_caption": ["a person riding a yellow surfboard on a wave. is it just 2 people? yes."], "negative_caption": ["a person riding a yellow surfboard on a wave. is it just 2 people? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3122", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000162035.jpg", "positive_caption": ["a sign on a sidewalk has a teddy bear on it. is it a stuffed bear? no."], "negative_caption": ["a sign on a sidewalk has a teddy bear on it. is it a stuffed bear? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7735", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000021396.jpg", "positive_caption": ["2 cats curled up together in a overstuffed chair sleeping. is it a color image? yes."], "negative_caption": ["2 cats curled up together in a overstuffed chair sleeping. is it a color image? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7479", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000385082.jpg", "positive_caption": ["small work space with desk and large monitor in non office setting. it is color picture? yes."], "negative_caption": ["small work space with desk and large monitor in non office setting. it is color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2293", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000251557.jpg", "positive_caption": ["a white toilet sitting next to a shower with a curtain. is this a big bathroom? no."], "negative_caption": ["a white toilet sitting next to a shower with a curtain. is this a big bathroom? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2972", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000317998.jpg", "positive_caption": ["a child with a tray walking past a buffet of fruits and vegetables. is it a color photo? yes."], "negative_caption": ["a child with a tray walking past a buffet of fruits and vegetables. is it a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_587", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000143713.jpg", "positive_caption": ["a young girl brushing an older woman's hair. is her hair gray? no."], "negative_caption": ["a young girl brushing an older woman's hair. is her hair gray? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5881", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000517793.jpg", "positive_caption": ["3 people fly a kite with smiley faces on it. is this photo in color? yes."], "negative_caption": ["3 people fly a kite with smiley faces on it. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7701", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000119145.jpg", "positive_caption": ["a couple of street signs and a traffic walk signal light. does it look like new york city? yes."], "negative_caption": ["a couple of street signs and a traffic walk signal light. does it look like new york city? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4811", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000090912.jpg", "positive_caption": ["a group of wine glasses sitting on a counter. is that glass of wine? yes."], "negative_caption": ["a group of wine glasses sitting on a counter. is that glass of wine? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4882", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000262736.jpg", "positive_caption": ["a dog is catching a frisbees in the air that was thrown to him. is this a big dog? no."], "negative_caption": ["a dog is catching a frisbees in the air that was thrown to him. is this a big dog? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10480", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000209864.jpg", "positive_caption": ["a man in an orange robe holding a red umbrella. is it raining in the image? no."], "negative_caption": ["a man in an orange robe holding a red umbrella. is it raining in the image? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8822", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000260699.jpg", "positive_caption": ["a gray parked truck with a brown and black dog standing in the back of it. is the dog have a collar on his neck? yes."], "negative_caption": ["a gray parked truck with a brown and black dog standing in the back of it. is the dog have a collar on his neck? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7539", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000137890.jpg", "positive_caption": ["a cat that is laying on a bed. is this a bed for a human? yes."], "negative_caption": ["a cat that is laying on a bed. is this a bed for a human? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6658", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000278922.jpg", "positive_caption": ["a pair of zebras runs in tall grass. are the zebras both adults? yes."], "negative_caption": ["a pair of zebras runs in tall grass. are the zebras both adults? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4044", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000269557.jpg", "positive_caption": ["the boy is checking his messages on the phone. is it outdoors? yes."], "negative_caption": ["the boy is checking his messages on the phone. is it outdoors? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6204", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000401963.jpg", "positive_caption": ["2 boats are placed on the cement near the ocean. are they big boats? no."], "negative_caption": ["2 boats are placed on the cement near the ocean. are they big boats? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2336", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000357567.jpg", "positive_caption": ["an open door showing a shower with the curtain closed. is this a bathroom? yes."], "negative_caption": ["an open door showing a shower with the curtain closed. is this a bathroom? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7395", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000019194.jpg", "positive_caption": ["an old, used refrigerator sits on a street curb. is this outside? yes."], "negative_caption": ["an old, used refrigerator sits on a street curb. is this outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1780", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000270024.jpg", "positive_caption": ["there is a man sitting on a couch in the living room. is this picture in color? yes."], "negative_caption": ["there is a man sitting on a couch in the living room. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6331", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000391531.jpg", "positive_caption": ["a white and red plant in a small vase on a table. is this indoors? yes."], "negative_caption": ["a white and red plant in a small vase on a table. is this indoors? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5876", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000147073.jpg", "positive_caption": ["a man in black coat walking by painting of a toaster. are their other people? no."], "negative_caption": ["a man in black coat walking by painting of a toaster. are their other people? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5341", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000099046.jpg", "positive_caption": ["a few people on bikes behind cows on a road. does this look like america? no."], "negative_caption": ["a few people on bikes behind cows on a road. does this look like america? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2290", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000427350.jpg", "positive_caption": ["a multi-image shot of a living room and it's objects. is it a large room? yes."], "negative_caption": ["a multi-image shot of a living room and it's objects. is it a large room? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3419", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000374563.jpg", "positive_caption": ["a few elephants standing around, a baby elephant with it's back turned to the camera. is this a zo? yes."], "negative_caption": ["a few elephants standing around, a baby elephant with it's back turned to the camera. is this a zo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2601", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000354126.jpg", "positive_caption": ["2 black and white dogs sleeping and stuffed play toys. are they inside? yes."], "negative_caption": ["2 black and white dogs sleeping and stuffed play toys. are they inside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_11065", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000094984.jpg", "positive_caption": ["a kitchen with a fridge and table inside of it. is this image in color? yes."], "negative_caption": ["a kitchen with a fridge and table inside of it. is this image in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1098", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000406873.jpg", "positive_caption": ["the man helps another person climb up onto the back of an elephant. is it daytime? yes."], "negative_caption": ["the man helps another person climb up onto the back of an elephant. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10043", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000193943.jpg", "positive_caption": ["a train goes along the tracks parallel to a highway. is this a color picture? yes."], "negative_caption": ["a train goes along the tracks parallel to a highway. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6824", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000169502.jpg", "positive_caption": ["there are many small stuffed animals in this picture. is it store? no."], "negative_caption": ["there are many small stuffed animals in this picture. is it store? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4513", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000572505.jpg", "positive_caption": ["a baseball player pitching a ball on top of a field. is this a pro player? yes."], "negative_caption": ["a baseball player pitching a ball on top of a field. is this a pro player? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4862", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000464964.jpg", "positive_caption": ["a giraffe is walking through the grass covered land. was this photo taken inside? no."], "negative_caption": ["a giraffe is walking through the grass covered land. was this photo taken inside? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4374", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000564061.jpg", "positive_caption": ["there are several pieces of luggage on a purple cart. can you see any people in this picture? no."], "negative_caption": ["there are several pieces of luggage on a purple cart. can you see any people in this picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10864", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000091487.jpg", "positive_caption": ["a number of zebras near 1 another in a field. are they in the wilderness? yes."], "negative_caption": ["a number of zebras near 1 another in a field. are they in the wilderness? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6368", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000476553.jpg", "positive_caption": ["a man and woman in formal wear next to a close of formal dresses. do they look like a couple? yes."], "negative_caption": ["a man and woman in formal wear next to a close of formal dresses. do they look like a couple? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4711", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000363272.jpg", "positive_caption": ["a man sitting on a stone block talking on a cell phone. is this scene in a park? no."], "negative_caption": ["a man sitting on a stone block talking on a cell phone. is this scene in a park? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8740", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000286292.jpg", "positive_caption": ["the big animal is walking through the town. is it a dog? no."], "negative_caption": ["the big animal is walking through the town. is it a dog? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1988", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000444543.jpg", "positive_caption": ["2 black and white bird standing on a nest. are they in a tree? no."], "negative_caption": ["2 black and white bird standing on a nest. are they in a tree? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9986", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000185890.jpg", "positive_caption": ["2 barefoot women holding game controllers in each hand. are they in the living room? no."], "negative_caption": ["2 barefoot women holding game controllers in each hand. are they in the living room? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_11080", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000137810.jpg", "positive_caption": ["an intersection with an icy road with no cars in sight. is this picture in color? no."], "negative_caption": ["an intersection with an icy road with no cars in sight. is this picture in color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10682", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000357860.jpg", "positive_caption": ["an oxen is carrying a load near trucks on a dirt area. is it daytime? yes."], "negative_caption": ["an oxen is carrying a load near trucks on a dirt area. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10710", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000184275.jpg", "positive_caption": ["a man hitting a baseball with a bat next to home plate. is this photo in color? yes."], "negative_caption": ["a man hitting a baseball with a bat next to home plate. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1322", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000283766.jpg", "positive_caption": ["an airplane sitting on the runway with the door open. is this indoors? no."], "negative_caption": ["an airplane sitting on the runway with the door open. is this indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6032", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000095061.jpg", "positive_caption": ["a bus parked in front of a house. are there people in this photo? no."], "negative_caption": ["a bus parked in front of a house. are there people in this photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3210", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000432453.jpg", "positive_caption": ["a man walking on a field carrying a baseball bat. is he a professional player? yes."], "negative_caption": ["a man walking on a field carrying a baseball bat. is he a professional player? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9983", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000577126.jpg", "positive_caption": ["a man sitting with 2 young boys eating hot dogs. is this indoors? no."], "negative_caption": ["a man sitting with 2 young boys eating hot dogs. is this indoors? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1854", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000490443.jpg", "positive_caption": ["a chair a surf board under an open umbrella. is this photo taken on a beach? yes."], "negative_caption": ["a chair a surf board under an open umbrella. is this photo taken on a beach? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4257", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000356125.jpg", "positive_caption": ["some very cute big elephants by some people. is this in a circus? no."], "negative_caption": ["some very cute big elephants by some people. is this in a circus? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9276", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000008647.jpg", "positive_caption": ["many different buildings near 1 another near trees. is this image in color? yes."], "negative_caption": ["many different buildings near 1 another near trees. is this image in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8496", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000058141.jpg", "positive_caption": ["people walking barefoot on a stone path holding umbrellas. is it raining? no."], "negative_caption": ["people walking barefoot on a stone path holding umbrellas. is it raining? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9395", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000068206.jpg", "positive_caption": ["a brush next to a tub full of water. is this picture in color? yes."], "negative_caption": ["a brush next to a tub full of water. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1480", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000535889.jpg", "positive_caption": ["a person standing up in a small room. is this in a house? yes."], "negative_caption": ["a person standing up in a small room. is this in a house? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9989", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000264183.jpg", "positive_caption": ["a large number of vases with different ribbons. is this a color picture? yes."], "negative_caption": ["a large number of vases with different ribbons. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6211", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000066444.jpg", "positive_caption": ["2 men in red uniforms on horses being stared at. is this picture in color? yes."], "negative_caption": ["2 men in red uniforms on horses being stared at. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1453", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000318924.jpg", "positive_caption": ["this is a picture of several different wild animals. is this a zoo picture? no."], "negative_caption": ["this is a picture of several different wild animals. is this a zoo picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6989", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000460049.jpg", "positive_caption": ["a train moving on a remote area with a river flowing next to the railway. is it a black and white picture? no."], "negative_caption": ["a train moving on a remote area with a river flowing next to the railway. is it a black and white picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8180", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000379159.jpg", "positive_caption": ["2 white boats next to each other in the water. it is picture color? no."], "negative_caption": ["2 white boats next to each other in the water. it is picture color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4462", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000129610.jpg", "positive_caption": ["some people are on the bleachers watching horses. is it a race? no."], "negative_caption": ["some people are on the bleachers watching horses. is it a race? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4489", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000397217.jpg", "positive_caption": ["a man sitting next to a beautiful women in front of a large sheet cake. is this outside? no."], "negative_caption": ["a man sitting next to a beautiful women in front of a large sheet cake. is this outside? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3943", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000057147.jpg", "positive_caption": ["an adult giraffe and a child giraffe standing near a fence. does this look like zoo? yes."], "negative_caption": ["an adult giraffe and a child giraffe standing near a fence. does this look like zoo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1395", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000255216.jpg", "positive_caption": ["husband and wife with bouquet in a pose. are they happy? yes."], "negative_caption": ["husband and wife with bouquet in a pose. are they happy? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3699", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000541901.jpg", "positive_caption": ["a skateboarder in a cement bowl during a trick. is this photo in color? yes."], "negative_caption": ["a skateboarder in a cement bowl during a trick. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3123", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000292835.jpg", "positive_caption": ["a bathroom that has a toilet and some nasty stuff all over. is this picture in color? yes."], "negative_caption": ["a bathroom that has a toilet and some nasty stuff all over. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3182", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000365999.jpg", "positive_caption": ["a yellow and black tennis racket and 3 balls and a net. are there any people in this photo? no."], "negative_caption": ["a yellow and black tennis racket and 3 balls and a net. are there any people in this photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1748", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000477639.jpg", "positive_caption": ["a pig and a sheep eating in black and white. are they eating side by side? no."], "negative_caption": ["a pig and a sheep eating in black and white. are they eating side by side? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5582", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000440500.jpg", "positive_caption": ["a small bird perched on top of a tree branch. is this photo in color? yes."], "negative_caption": ["a small bird perched on top of a tree branch. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8481", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000100918.jpg", "positive_caption": ["a freight train sitting idle on the track. is it old looking? yes."], "negative_caption": ["a freight train sitting idle on the track. is it old looking? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4346", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000018916.jpg", "positive_caption": ["a tent in the woods during the daytime. is it forest? yes."], "negative_caption": ["a tent in the woods during the daytime. is it forest? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7076", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000473060.jpg", "positive_caption": ["a male skateboarder wearing black is doing a trick. is he wearing a helmet? no."], "negative_caption": ["a male skateboarder wearing black is doing a trick. is he wearing a helmet? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5835", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000110530.jpg", "positive_caption": ["a man in a pink bow tie and a pink shirt is being hugged by a man in a blue shirt. is this a color image? yes."], "negative_caption": ["a man in a pink bow tie and a pink shirt is being hugged by a man in a blue shirt. is this a color image? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1862", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000458048.jpg", "positive_caption": ["some pizzas in boxes are arranged on a table. is this a color photo? yes."], "negative_caption": ["some pizzas in boxes are arranged on a table. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10453", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000278639.jpg", "positive_caption": ["a picture of a bed that is in a room. is this a large bed? no."], "negative_caption": ["a picture of a bed that is in a room. is this a large bed? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2246", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000350987.jpg", "positive_caption": ["a red and white jet on a runway and brown grass. can you see any people in this photo? no."], "negative_caption": ["a red and white jet on a runway and brown grass. can you see any people in this photo? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4793", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000042371.jpg", "positive_caption": ["a man sits on top of a buggy with horses while other people look around the farmer's market. is it old-time wagon? yes."], "negative_caption": ["a man sits on top of a buggy with horses while other people look around the farmer's market. is it old-time wagon? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5004", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000334936.jpg", "positive_caption": ["a person riding a motorcycle in a body of water. are they on street? no."], "negative_caption": ["a person riding a motorcycle in a body of water. are they on street? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2607", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000262103.jpg", "positive_caption": ["a medium sized dog walking by itself on the street. is this taking place on a farm? no."], "negative_caption": ["a medium sized dog walking by itself on the street. is this taking place on a farm? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4282", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000518701.jpg", "positive_caption": ["a room with a bed and a very large window. is this photo in color? yes."], "negative_caption": ["a room with a bed and a very large window. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10509", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000157301.jpg", "positive_caption": ["a large white airplane parked in a stationary position. is it a passenger plane? yes."], "negative_caption": ["a large white airplane parked in a stationary position. is it a passenger plane? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1479", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000371134.jpg", "positive_caption": ["1 plane taking off and another ready to land. is this an airport? yes."], "negative_caption": ["1 plane taking off and another ready to land. is this an airport? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6626", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000097010.jpg", "positive_caption": ["there are 2 skiers that are waiting at the train station. are they wearing hats? no."], "negative_caption": ["there are 2 skiers that are waiting at the train station. are they wearing hats? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3185", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000434221.jpg", "positive_caption": ["a red, double decker bus is going down the street. is it a big bus? yes."], "negative_caption": ["a red, double decker bus is going down the street. is it a big bus? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3553", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000494759.jpg", "positive_caption": ["2 people standing on a sandy beach flying a kite. are they dressed for summer? no."], "negative_caption": ["2 people standing on a sandy beach flying a kite. are they dressed for summer? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8242", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000496696.jpg", "positive_caption": ["there is a large herd of cattle walking down the dirt road. is this a color picture? yes."], "negative_caption": ["there is a large herd of cattle walking down the dirt road. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4646", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000551082.jpg", "positive_caption": ["a table with several plates on it including sliced fruit and pancakes. does the table have a tablecloth on it? no."], "negative_caption": ["a table with several plates on it including sliced fruit and pancakes. does the table have a tablecloth on it? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6246", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000580104.jpg", "positive_caption": ["a man that is holding a phone in his hand. is this a color photo? yes."], "negative_caption": ["a man that is holding a phone in his hand. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6720", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000190914.jpg", "positive_caption": ["2 people are playing a video game together. both are male? no."], "negative_caption": ["2 people are playing a video game together. both are male? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7079", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000424982.jpg", "positive_caption": ["a sign that is in the middle of the street. can you see any people in this picture? no."], "negative_caption": ["a sign that is in the middle of the street. can you see any people in this picture? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6391", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000283426.jpg", "positive_caption": ["an airplane from korean air is painted in blue. is this plane in the air? no."], "negative_caption": ["an airplane from korean air is painted in blue. is this plane in the air? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_173", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000569774.jpg", "positive_caption": ["a woman and children preparing a meal together. are they inside? yes."], "negative_caption": ["a woman and children preparing a meal together. are they inside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6258", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000222324.jpg", "positive_caption": ["a person holding a lit candle while standing underneath a red umbrella. is it raining? yes."], "negative_caption": ["a person holding a lit candle while standing underneath a red umbrella. is it raining? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4264", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000231466.jpg", "positive_caption": ["a dog on a boat riding through the city of venice. is it in color? yes."], "negative_caption": ["a dog on a boat riding through the city of venice. is it in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4409", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000304833.jpg", "positive_caption": ["2 elephants that are standing in the grass. are they both the same size? yes."], "negative_caption": ["2 elephants that are standing in the grass. are they both the same size? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1656", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000023899.jpg", "positive_caption": ["3 young men playing wii on a projection television. is this picture in color? yes."], "negative_caption": ["3 young men playing wii on a projection television. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9005", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000574499.jpg", "positive_caption": ["a herd of cattle grazing near a hut. is it sunny? yes."], "negative_caption": ["a herd of cattle grazing near a hut. is it sunny? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5236", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000197063.jpg", "positive_caption": ["skateboarder inspects a bench while holding his board. is it sunny out? no."], "negative_caption": ["skateboarder inspects a bench while holding his board. is it sunny out? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1338", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000408138.jpg", "positive_caption": ["the front of a bus behind a fence. is this a working bus? yes."], "negative_caption": ["the front of a bus behind a fence. is this a working bus? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8284", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000333412.jpg", "positive_caption": ["this looks like the setting of an outdoor meeting place. is this a restaurant? no."], "negative_caption": ["this looks like the setting of an outdoor meeting place. is this a restaurant? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9180", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000027569.jpg", "positive_caption": ["3 skiers walking through the snow carrying their skis. are they facing the camera? no."], "negative_caption": ["3 skiers walking through the snow carrying their skis. are they facing the camera? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9538", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000024343.jpg", "positive_caption": ["2 people on motorcycles car and trees and water. do they have helmets? yes."], "negative_caption": ["2 people on motorcycles car and trees and water. do they have helmets? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10997", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000557355.jpg", "positive_caption": ["candles lit on a birthday cake with many people looking on. is this a round cake? yes."], "negative_caption": ["candles lit on a birthday cake with many people looking on. is this a round cake? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5138", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000199516.jpg", "positive_caption": ["a woman taking a picture of a cow that's leaned over some rocks. is it sunny? no."], "negative_caption": ["a woman taking a picture of a cow that's leaned over some rocks. is it sunny? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9304", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000521471.jpg", "positive_caption": ["a photo take from the airport looking at a plane at a terminal. is it crowded? no."], "negative_caption": ["a photo take from the airport looking at a plane at a terminal. is it crowded? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4921", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000402726.jpg", "positive_caption": ["an air force officer is handling a suitcase. is it a man? yes."], "negative_caption": ["an air force officer is handling a suitcase. is it a man? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2037", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000215315.jpg", "positive_caption": ["2 adult elephants and 1 young elephant are in a zoo. are they outside? yes."], "negative_caption": ["2 adult elephants and 1 young elephant are in a zoo. are they outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2536", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000008321.jpg", "positive_caption": ["someone is holding a computer on top of 2 plastic barrels. can you see their face? no."], "negative_caption": ["someone is holding a computer on top of 2 plastic barrels. can you see their face? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7081", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000489961.jpg", "positive_caption": ["a close up of a 1 way sign in the city. is this outside? yes."], "negative_caption": ["a close up of a 1 way sign in the city. is this outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4662", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000149551.jpg", "positive_caption": ["a big silver and colorfully printed elephant sits alongside a walkway. is this a cartoon? no."], "negative_caption": ["a big silver and colorfully printed elephant sits alongside a walkway. is this a cartoon? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1198", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000299411.jpg", "positive_caption": ["the bathroom has red carpet and yellowish appliances. is this photo? yes."], "negative_caption": ["the bathroom has red carpet and yellowish appliances. is this photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6871", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000049217.jpg", "positive_caption": ["a man wearing short sleeves is skiing in the snow. is he wearing a jacket? no."], "negative_caption": ["a man wearing short sleeves is skiing in the snow. is he wearing a jacket? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6619", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000137320.jpg", "positive_caption": ["the vegetables on the table are next to some bananas. is this in a store? no."], "negative_caption": ["the vegetables on the table are next to some bananas. is this in a store? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1734", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000502114.jpg", "positive_caption": ["2 little girls outside holding their umbrellas. is it raining? no."], "negative_caption": ["2 little girls outside holding their umbrellas. is it raining? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2956", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000304698.jpg", "positive_caption": ["several open suitcases sitting on the hotel room floor. is it well lit? yes."], "negative_caption": ["several open suitcases sitting on the hotel room floor. is it well lit? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9743", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000407949.jpg", "positive_caption": ["a man in a suit holding the door to a train open. is he in uniform? yes."], "negative_caption": ["a man in a suit holding the door to a train open. is he in uniform? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1980", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000517534.jpg", "positive_caption": ["an elephant with 2 calf take cover from sunshine. are they under a tree? yes."], "negative_caption": ["an elephant with 2 calf take cover from sunshine. are they under a tree? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6756", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000168377.jpg", "positive_caption": ["a girl flying a kite on a grassy hill. is this an older girl? no."], "negative_caption": ["a girl flying a kite on a grassy hill. is this an older girl? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_629", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000033034.jpg", "positive_caption": ["a piece of bread holding various foods that include sauce and a salad. is it a sandwich? no."], "negative_caption": ["a piece of bread holding various foods that include sauce and a salad. is it a sandwich? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1909", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000063185.jpg", "positive_caption": ["a man in black vest waterskiing with trees in background. is this a color photo? yes."], "negative_caption": ["a man in black vest waterskiing with trees in background. is this a color photo? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3195", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000061184.jpg", "positive_caption": ["a pool next to a couple of wooden chairs. is this an outdoor pool? yes."], "negative_caption": ["a pool next to a couple of wooden chairs. is this an outdoor pool? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5944", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000365115.jpg", "positive_caption": ["a bacon cheeseburger with a donut as the bun. hi, can you see any people in this image? no."], "negative_caption": ["a bacon cheeseburger with a donut as the bun. hi, can you see any people in this image? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_752", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000223112.jpg", "positive_caption": ["a plate with crab cakes and some sort of pie. is it a close up of the food? yes."], "negative_caption": ["a plate with crab cakes and some sort of pie. is it a close up of the food? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4913", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000386257.jpg", "positive_caption": ["large circular shaped clock tower in black and white. is it daytime? no."], "negative_caption": ["large circular shaped clock tower in black and white. is it daytime? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7499", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000318209.jpg", "positive_caption": ["a plate of food and a drink on a surface. is this photo in color? yes."], "negative_caption": ["a plate of food and a drink on a surface. is this photo in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8455", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000558365.jpg", "positive_caption": ["a ship out on the water with another ship in the distance behind it. is it a sea? yes."], "negative_caption": ["a ship out on the water with another ship in the distance behind it. is it a sea? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1896", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000125979.jpg", "positive_caption": ["a white plate a fork a piece of cake and whip cream. is this part of a birthday cake? no."], "negative_caption": ["a white plate a fork a piece of cake and whip cream. is this part of a birthday cake? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3692", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000315211.jpg", "positive_caption": ["a green street sign next to a neon sign on a building. dose sign have any writing on it? yes."], "negative_caption": ["a green street sign next to a neon sign on a building. dose sign have any writing on it? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5486", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000014128.jpg", "positive_caption": ["a young woman perched upon a white fire hydrant posing with her arms stretched out. does she have boots on? no."], "negative_caption": ["a young woman perched upon a white fire hydrant posing with her arms stretched out. does she have boots on? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1381", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000112137.jpg", "positive_caption": ["some baseball players are playing baseball on a field. is this picture in color? yes."], "negative_caption": ["some baseball players are playing baseball on a field. is this picture in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4363", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000262951.jpg", "positive_caption": ["people flying kits at the beach with a clear blue sky. does this photo have a watermark? no."], "negative_caption": ["people flying kits at the beach with a clear blue sky. does this photo have a watermark? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4168", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000473896.jpg", "positive_caption": ["a clock tower sitting on top of a building. is this a church? no."], "negative_caption": ["a clock tower sitting on top of a building. is this a church? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9192", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000067987.jpg", "positive_caption": ["fruit sitting on a plate arranged to look like a smile. is it a happy smile? yes."], "negative_caption": ["fruit sitting on a plate arranged to look like a smile. is it a happy smile? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6935", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000502916.jpg", "positive_caption": ["a woman standing on top of a tennis court with a racquet. is she swinging? yes."], "negative_caption": ["a woman standing on top of a tennis court with a racquet. is she swinging? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1735", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000486125.jpg", "positive_caption": ["a young man fastening a tie, with the expression of 1 who doesn't appreciate ties. is this a color picture? yes."], "negative_caption": ["a young man fastening a tie, with the expression of 1 who doesn't appreciate ties. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6247", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000244659.jpg", "positive_caption": ["a bunch of people standing around at the beach with a kite in the air. is it sunny? no."], "negative_caption": ["a bunch of people standing around at the beach with a kite in the air. is it sunny? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1652", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000028924.jpg", "positive_caption": ["a tennis court that has a girl and a racket. is this court outside? yes."], "negative_caption": ["a tennis court that has a girl and a racket. is this court outside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1170", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000298170.jpg", "positive_caption": ["a train coming down the tracks in the country. is it a passenger train? no."], "negative_caption": ["a train coming down the tracks in the country. is it a passenger train? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_4507", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000233110.jpg", "positive_caption": ["a electric company repair truck on the side of the road. is this a color picture? yes."], "negative_caption": ["a electric company repair truck on the side of the road. is this a color picture? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5533", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000123719.jpg", "positive_caption": ["a glass vase sits on a table with chairs. is there water in it? no."], "negative_caption": ["a glass vase sits on a table with chairs. is there water in it? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_1668", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000107781.jpg", "positive_caption": ["an overview of a game of tennis with a crowd watching. can you see both players? no."], "negative_caption": ["an overview of a game of tennis with a crowd watching. can you see both players? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_8160", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000119647.jpg", "positive_caption": ["a woman holding a phone to her ear while in the street. is it daytime? yes."], "negative_caption": ["a woman holding a phone to her ear while in the street. is it daytime? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_2877", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000218145.jpg", "positive_caption": ["a guy is cutting something out of a piece of paper. is it a newspaper? no."], "negative_caption": ["a guy is cutting something out of a piece of paper. is it a newspaper? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5641", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000002664.jpg", "positive_caption": ["bike made with lounge chair on top for passenger to ride in. is it motorized? no."], "negative_caption": ["bike made with lounge chair on top for passenger to ride in. is it motorized? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7089", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000262651.jpg", "positive_caption": ["a large ship is pulled up to a container dock. is this image in color? yes."], "negative_caption": ["a large ship is pulled up to a container dock. is this image in color? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9363", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000078565.jpg", "positive_caption": ["we see a very old picture of people enjoying the shore. is it in black and white? yes."], "negative_caption": ["we see a very old picture of people enjoying the shore. is it in black and white? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9189", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000349559.jpg", "positive_caption": ["a teenage boy is riding on the street with a skateboard. is this photo in color? no."], "negative_caption": ["a teenage boy is riding on the street with a skateboard. is this photo in color? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9747", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000443844.jpg", "positive_caption": ["a man in white shirt doing a trick on a skateboard. does he have a helmet on? no."], "negative_caption": ["a man in white shirt doing a trick on a skateboard. does he have a helmet on? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_9222", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000306554.jpg", "positive_caption": ["a white fluffy cat sleeps while wearing a knitted hat. is this inside? yes."], "negative_caption": ["a white fluffy cat sleeps while wearing a knitted hat. is this inside? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5020", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_val2014_000000109488.jpg", "positive_caption": ["a case with a pink and green pattern. is it a suitcase? no."], "negative_caption": ["a case with a pink and green pattern. is it a suitcase? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_10038", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000364803.jpg", "positive_caption": ["a variety of vegetables are on a kitchen counter. is this in kitchen? yes."], "negative_caption": ["a variety of vegetables are on a kitchen counter. is this in kitchen? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_6642", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000101069.jpg", "positive_caption": ["a long train going down the tracks through a town. is it a passenger train? yes."], "negative_caption": ["a long train going down the tracks through a town. is it a passenger train? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_5368", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000260932.jpg", "positive_caption": ["a woman and man changing a microphone on a field near a baseball player. are they changing a microphone? yes."], "negative_caption": ["a woman and man changing a microphone on a field near a baseball player. are they changing a microphone? no."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_3135", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "VisDial_v1.0/train/COCO_train2014_000000268733.jpg", "positive_caption": ["a pair of orange scissors next to a cut up credit car. is this photo in black and white? no."], "negative_caption": ["a pair of orange scissors next to a cut up credit car. is this photo in black and white? yes."], "original_file_name": "coreference-standard", "dataset": "VisDial_v1.0", "key": "coref_train_7020", "linguistic_phenomena": "coreference", "original_split": "train"}
{"image_file_name": "visual7w/v7w_1.jpg", "positive_caption": ["There are exactly 4 cars parked."], "negative_caption": ["There are exactly 0 cars parked."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360136.jpg", "positive_caption": ["There are exactly 4 tomatoes pictured."], "negative_caption": ["There is exactly 1 tomato pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2360136", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360434.jpg", "positive_caption": ["There are exactly 4 signs pictured."], "negative_caption": ["There are exactly 1 signs pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2360434", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360457.jpg", "positive_caption": ["There are exactly 4 kites in the sky."], "negative_caption": ["There are exactly 2 kites in the sky."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2360457", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360508.jpg", "positive_caption": ["There are exactly 4 of the birds wings extended in total."], "negative_caption": ["There is exactly 1 of the birds wing extended in total."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2360508", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360734.jpg", "positive_caption": ["There are exactly 4 people in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2360734", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360933.jpg", "positive_caption": ["There are exactly 4 floor grates visible."], "negative_caption": ["There are exactly 2 floor grates visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2360933", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361175.jpg", "positive_caption": ["There are exactly 4 windows and doors."], "negative_caption": ["There are exactly 3 windows and doors."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2361175", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361244.jpg", "positive_caption": ["There are exactly 4 zebras in photo."], "negative_caption": ["There are exactly 0 zebras in photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2361244", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361375.jpg", "positive_caption": ["There are exactly 4 people in this picture."], "negative_caption": ["There are exactly 2 people in this picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2361375", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361437.jpg", "positive_caption": ["There are exactly 4 cows shown."], "negative_caption": ["There is exactly 1 cow shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2361437", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362476.jpg", "positive_caption": ["There are exactly 4 eagles visible."], "negative_caption": ["There are exactly 0 eagles visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2362476", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362752.jpg", "positive_caption": ["There are exactly 5 skateboarders."], "negative_caption": ["There are exactly 0 skateboarders."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2362752", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363037.jpg", "positive_caption": ["There are exactly 4 players."], "negative_caption": ["There is exactly 1 player."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2363037", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363712.jpg", "positive_caption": ["You see exactly 4 horses in the image."], "negative_caption": ["You see exactly 0 horses in the image."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2363712", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363721.jpg", "positive_caption": ["There are exactly 4 boards behind her."], "negative_caption": ["There are exactly 3 boards behind her."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2363721", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363965.jpg", "positive_caption": ["Exactly 4 ford logos can be seen."], "negative_caption": ["Exactly 1 ford logo can be seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2363965", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363971.jpg", "positive_caption": ["There are exactly 4 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2363971", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364009.jpg", "positive_caption": ["There are exactly 7 women in the photo."], "negative_caption": ["There is exactly 1 woman in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2364009", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364922.jpg", "positive_caption": ["There are exactly 4 pizzas."], "negative_caption": ["There are exactly 0 pizzas."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2364922", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365208.jpg", "positive_caption": ["There are exactly 4 people on the elephants."], "negative_caption": ["There are exactly 0 people on the elephants."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2365208", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365548.jpg", "positive_caption": ["There are exactly 4 people pictured."], "negative_caption": ["There is exactly 1 person pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2365548", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366034.jpg", "positive_caption": ["There are exactly 4 pillows."], "negative_caption": ["There is exactly 1 pillow."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2366034", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366163.jpg", "positive_caption": ["There are exactly 4 windows visible."], "negative_caption": ["There are exactly 3 windows visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2366163", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366253.jpg", "positive_caption": ["There are exactly 6 people in the photo."], "negative_caption": ["There are exactly 0 people in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2366253", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366671.jpg", "positive_caption": ["There are exactly 4 lights visible."], "negative_caption": ["There are exactly 2 lights visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2366671", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367490.jpg", "positive_caption": ["There are exactly 4 motorcycles."], "negative_caption": ["There are exactly 3 motorcycles."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2367490", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367942.jpg", "positive_caption": ["There are exactly 4 propellers on the plane."], "negative_caption": ["There are exactly 0 propellers on the plane."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2367942", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368931.jpg", "positive_caption": ["There are exactly 4 planes in the picture."], "negative_caption": ["There are exactly 0 planes in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2368931", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369128.jpg", "positive_caption": ["There are exactly 4 zebras."], "negative_caption": ["There is exactly 1 zebra."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2369128", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369658.jpg", "positive_caption": ["There are exactly 8 toys on the bed."], "negative_caption": ["There is exactly 1 toy on the bed."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2369658", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370774.jpg", "positive_caption": ["There are exactly 4 planes in the picture."], "negative_caption": ["There are exactly 0 planes in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2370774", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370873.jpg", "positive_caption": ["There are exactly 4 plates shown in the photo."], "negative_caption": ["There is exactly 1 plate shown in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2370873", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372073.jpg", "positive_caption": ["There are exactly 4 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2372073", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372473.jpg", "positive_caption": ["There are exactly 4 scooters in the photo."], "negative_caption": ["There is exactly 1 scooter in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2372473", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372620.jpg", "positive_caption": ["There are exactly 4 kites flying."], "negative_caption": ["There are exactly 0 kites flying."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2372620", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372786.jpg", "positive_caption": ["There are exactly 4 plates shown."], "negative_caption": ["There are exactly 0 plates shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2372786", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373128.jpg", "positive_caption": ["There are exactly 4 pieces of food on the plate."], "negative_caption": ["There are exactly 3 pieces of food on the plate."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2373128", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373481.jpg", "positive_caption": ["There are exactly 4 containers show food."], "negative_caption": ["There are exactly 0 containers show food."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2373481", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374607.jpg", "positive_caption": ["There are exactly 4 people in this image."], "negative_caption": ["There are exactly 3 people in this image."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2374607", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375061.jpg", "positive_caption": ["You see exactly 4 heads."], "negative_caption": ["You see exactly 2 heads."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2375061", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375160.jpg", "positive_caption": ["There are exactly 4 buildings."], "negative_caption": ["There are exactly 2 buildings."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2375160", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375454.jpg", "positive_caption": ["There are exactly 4 dishes in the picture."], "negative_caption": ["There is exactly 1 dish in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2375454", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375642.jpg", "positive_caption": ["There are exactly 4 people visible."], "negative_caption": ["There are exactly 0 people visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2375642", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375837.jpg", "positive_caption": ["There are exactly 4 writing utensils clearly visible."], "negative_caption": ["There are exactly 0 writing utensils clearly visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2375837", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377779.jpg", "positive_caption": ["There are exactly 4 pieces."], "negative_caption": ["There are exactly 2 pieces."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2377779", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378084.jpg", "positive_caption": ["There are exactly 4 elephants."], "negative_caption": ["There are exactly 3 elephants."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2378084", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592325.jpg", "positive_caption": ["There are exactly 4 red lights on."], "negative_caption": ["There are exactly 0 red lights on."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592325", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378887.jpg", "positive_caption": ["There are exactly 4 men playing."], "negative_caption": ["There are exactly 3 men playing."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2378887", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592557.jpg", "positive_caption": ["There are exactly 4 cones."], "negative_caption": ["There is exactly 1 cone."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592557", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379053.jpg", "positive_caption": ["There are exactly 6 people visible."], "negative_caption": ["There are exactly 2 people visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2379053", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592643.jpg", "positive_caption": ["There are exactly 8 boxes on the refrigerator."], "negative_caption": ["There are exactly 2 boxes on the refrigerator."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592643", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592835.jpg", "positive_caption": ["There are exactly 4 chairs."], "negative_caption": ["There is exactly 1 chair."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592835", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379433.jpg", "positive_caption": ["There are exactly 4 wheels on the skateboard."], "negative_caption": ["There is exactly 1 wheel on the skateboard."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2379433", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379573.jpg", "positive_caption": ["There are exactly 4 train tracks."], "negative_caption": ["There are exactly 3 train tracks."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2379573", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379640.jpg", "positive_caption": ["There are exactly 4 pillows."], "negative_caption": ["There are exactly 2 pillows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2379640", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380605.jpg", "positive_caption": ["There are exactly 4 birds pictured."], "negative_caption": ["There are exactly 0 birds pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2380605", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380782.jpg", "positive_caption": ["There are exactly 4 horses."], "negative_caption": ["There are exactly 3 horses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2380782", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381178.jpg", "positive_caption": ["There are exactly 4 signs on the post."], "negative_caption": ["There are exactly 2 signs on the post."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2381178", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381614.jpg", "positive_caption": ["There are exactly 4 kinds of vegetables shown."], "negative_caption": ["There are exactly 3 kinds of vegetables shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2381614", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381926.jpg", "positive_caption": ["There are exactly 4 boats shown."], "negative_caption": ["There are exactly 0 boats shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2381926", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382639.jpg", "positive_caption": ["There are exactly 7 pots on the top shelf."], "negative_caption": ["There is exactly 1 pot on the top shelf."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2382639", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285933.jpg", "positive_caption": ["There are exactly 4 blueberries."], "negative_caption": ["There is exactly 1 blueberry."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_285933", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383290.jpg", "positive_caption": ["There are exactly 4 flower stems."], "negative_caption": ["There are exactly 0 flower stems."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2383290", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384549.jpg", "positive_caption": ["There are exactly 4 boats in the picture."], "negative_caption": ["There are exactly 2 boats in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2384549", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384955.jpg", "positive_caption": ["There are exactly 4 cows in the picture."], "negative_caption": ["There are exactly 3 cows in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2384955", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385676.jpg", "positive_caption": ["There are exactly 9 pieces of fruit."], "negative_caption": ["There are exactly 0 pieces of fruit."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2385676", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385700.jpg", "positive_caption": ["There are exactly 4 leaves on the pizza."], "negative_caption": ["There is exactly 1 leave on the pizza."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2385700", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385975.jpg", "positive_caption": ["There are exactly 4 colors."], "negative_caption": ["There are exactly 2 colors."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2385975", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386171.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2386171", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386605.jpg", "positive_caption": ["Exactly 4 people can be seen on the bus."], "negative_caption": ["Exactly 2 people can be seen on the bus."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2386605", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386811.jpg", "positive_caption": ["There are exactly 4 jets."], "negative_caption": ["There is exactly 1 jet."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2386811", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387063.jpg", "positive_caption": ["There are exactly 4 people here."], "negative_caption": ["There are exactly 3 people here."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2387063", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387414.jpg", "positive_caption": ["There are exactly 4 tires."], "negative_caption": ["There are exactly 0 tires."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2387414", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388051.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2388051", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389022.jpg", "positive_caption": ["There are exactly 4 legs on the seat."], "negative_caption": ["There are exactly 2 legs on the seat."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2389022", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389519.jpg", "positive_caption": ["There are exactly 4 bikes on the rack."], "negative_caption": ["There are exactly 2 bikes on the rack."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2389519", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389881.jpg", "positive_caption": ["There are exactly 4 windows visible."], "negative_caption": ["There are exactly 3 windows visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2389881", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391208.jpg", "positive_caption": ["There are exactly 4 zebras in the picture."], "negative_caption": ["There is exactly 1 zebra in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2391208", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391321.jpg", "positive_caption": ["There are exactly 4 cows."], "negative_caption": ["There is exactly 1 cow."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2391321", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391448.jpg", "positive_caption": ["There are exactly 4 giraffes in this picture."], "negative_caption": ["There are exactly 2 giraffes in this picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2391448", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392217.jpg", "positive_caption": ["There are exactly 4 people standing on the stone surface in the foreground of the photo."], "negative_caption": ["There are exactly 0 people standing on the stone surface in the foreground of the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2392217", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392484.jpg", "positive_caption": ["There are exactly 4 shoes shown."], "negative_caption": ["There is exactly 1 shoe shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2392484", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393355.jpg", "positive_caption": ["There are exactly 4 players or shown."], "negative_caption": ["There are exactly 2 players or shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2393355", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393653.jpg", "positive_caption": ["There are exactly 4 colors in the girl's shirt."], "negative_caption": ["There are exactly 2 colors in the girl's shirt."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2393653", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394602.jpg", "positive_caption": ["There are exactly 4 women in the picture."], "negative_caption": ["There are exactly 1 women in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2394602", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395593.jpg", "positive_caption": ["There are exactly 4 peppers in the picture."], "negative_caption": ["There are exactly 3 peppers in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2395593", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397608.jpg", "positive_caption": ["There are exactly 4 vases shown."], "negative_caption": ["There are exactly 3 vases shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2397608", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398034.jpg", "positive_caption": ["There are exactly 4 stars on flag."], "negative_caption": ["There are exactly 2 stars on flag."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2398034", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398295.jpg", "positive_caption": ["There are exactly 4 cows."], "negative_caption": ["There are exactly 3 cows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2398295", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398382.jpg", "positive_caption": ["There are exactly 4 zebras."], "negative_caption": ["There is exactly 1 zebra."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2398382", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398455.jpg", "positive_caption": ["There are exactly 4 players."], "negative_caption": ["There are exactly 3 players."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2398455", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398592.jpg", "positive_caption": ["There are exactly 4 umbrellas."], "negative_caption": ["There are exactly 0 umbrellas."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2398592", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398674.jpg", "positive_caption": ["There are exactly 12 kids in the pic."], "negative_caption": ["There are exactly 2 kids in the pic."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2398674", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398773.jpg", "positive_caption": ["There are exactly 7 sides of the octagon shown."], "negative_caption": ["There is exactly 1 side of the octagon shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2398773", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399158.jpg", "positive_caption": ["There are exactly 4 benches."], "negative_caption": ["There are exactly 2 benches."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2399158", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401086.jpg", "positive_caption": ["There are exactly 4 giraffes at least partially visible."], "negative_caption": ["There are exactly 0 giraffes at least partially visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401086", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401445.jpg", "positive_caption": ["There are exactly 6 surfboards shown."], "negative_caption": ["There is exactly 1 surfboard shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401445", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401498.jpg", "positive_caption": ["There are exactly 4 knobs on the stove."], "negative_caption": ["There are exactly 2 knobs on the stove."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401498", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401779.jpg", "positive_caption": ["There are exactly 4 bears."], "negative_caption": ["There is exactly 1 bear."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401779", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401974.jpg", "positive_caption": ["There are exactly 4 chimneys."], "negative_caption": ["There are exactly 0 chimneys."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401974", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402074.jpg", "positive_caption": ["There are exactly 4 red vehicles."], "negative_caption": ["There are exactly 2 red vehicles."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2402074", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402597.jpg", "positive_caption": ["There are exactly 4 people in the truck."], "negative_caption": ["There are exactly 3 people in the truck."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2402597", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402653.jpg", "positive_caption": ["There are exactly 4 glasses in the photo."], "negative_caption": ["There are exactly 3 glasses in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2402653", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403538.jpg", "positive_caption": ["There are exactly 4 slices of pizza."], "negative_caption": ["There is exactly 1 slice of pizza."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2403538", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403594.jpg", "positive_caption": ["There are exactly 4 cows."], "negative_caption": ["There is exactly 1 cow."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2403594", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403793.jpg", "positive_caption": ["There are exactly 4 wheels on the skateboard."], "negative_caption": ["There are exactly 2 wheels on the skateboard."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2403793", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344871.jpg", "positive_caption": ["There are exactly 4 people shown."], "negative_caption": ["There are exactly 0 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344871", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404285.jpg", "positive_caption": ["There are exactly 4 kids."], "negative_caption": ["There are exactly 3 kids."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2404285", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404436.jpg", "positive_caption": ["There are exactly 5 cell phones on the table."], "negative_caption": ["There are exactly 2 cell phones on the table."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2404436", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404678.jpg", "positive_caption": ["There are exactly 4 flowers in the vase."], "negative_caption": ["There are exactly 2 flowers in the vase."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2404678", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405440.jpg", "positive_caption": ["There are exactly 4 people in the photo."], "negative_caption": ["There are exactly 0 people in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2405440", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405906.jpg", "positive_caption": ["There are exactly 4 animals total."], "negative_caption": ["There are exactly 2 animals total."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2405906", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406002.jpg", "positive_caption": ["There are exactly 8 tomatoes on the plate."], "negative_caption": ["There are exactly 3 tomatoes on the plate."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2406002", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406900.jpg", "positive_caption": ["There are exactly 4 lamps."], "negative_caption": ["There are exactly 3 lamps."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2406900", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408431.jpg", "positive_caption": ["There are exactly 4 strings on the kite."], "negative_caption": ["There are exactly 3 strings on the kite."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2408431", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409674.jpg", "positive_caption": ["There are exactly 4 knobs visible."], "negative_caption": ["There is exactly 1 knob visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2409674", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409813.jpg", "positive_caption": ["There are exactly 4 round glass containers."], "negative_caption": ["There are exactly 2 round glass containers."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2409813", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411479.jpg", "positive_caption": ["There are exactly 4 doughnuts appear to be yellow."], "negative_caption": ["There are exactly 2 doughnuts appear to be yellow."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2411479", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411942.jpg", "positive_caption": ["There are exactly 4 zebras in the picture."], "negative_caption": ["There is exactly 1 zebra in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2411942", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412169.jpg", "positive_caption": ["There are exactly 18 windows visible on the building."], "negative_caption": ["There is exactly 1 window visible on the building."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2412169", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412204.jpg", "positive_caption": ["There are exactly 4 people seated."], "negative_caption": ["There is exactly 1 person seated."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2412204", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413772.jpg", "positive_caption": ["There are exactly 4 people standing on the tennis court."], "negative_caption": ["There are exactly 2 people standing on the tennis court."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2413772", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414180.jpg", "positive_caption": ["There are exactly 4 people in the image."], "negative_caption": ["There is exactly 1 person in the image."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2414180", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415024.jpg", "positive_caption": ["There are exactly 4 windows around the vines."], "negative_caption": ["There are exactly 2 windows around the vines."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2415024", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415056.jpg", "positive_caption": ["There are exactly 4 tracks shown."], "negative_caption": ["There are exactly 2 tracks shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2415056", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415803.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2415803", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416742.jpg", "positive_caption": ["There are exactly 4 people visible."], "negative_caption": ["There are exactly 2 people visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2416742", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416821.jpg", "positive_caption": ["There are exactly 4 flowers in the vase."], "negative_caption": ["There are exactly 3 flowers in the vase."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2416821", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_712985.jpg", "positive_caption": ["There are exactly 5 vehicles on the road."], "negative_caption": ["There are exactly 2 vehicles on the road."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_712985", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713003.jpg", "positive_caption": ["There are exactly 4 men in the pictures."], "negative_caption": ["There are exactly 2 men in the pictures."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_713003", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713092.jpg", "positive_caption": ["There are exactly 4 buses."], "negative_caption": ["There are exactly 0 buses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_713092", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713265.jpg", "positive_caption": ["There are exactly 6 people in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_713265", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417216.jpg", "positive_caption": ["There are exactly 4 men on the field."], "negative_caption": ["There is exactly 1 man on the field."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2417216", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417412.jpg", "positive_caption": ["There are exactly 4 colors on the bird."], "negative_caption": ["There are exactly 3 colors on the bird."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2417412", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417455.jpg", "positive_caption": ["There are exactly 4 plates on the table."], "negative_caption": ["There are exactly 0 plates on the table."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2417455", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315587.jpg", "positive_caption": ["There are exactly 4 planes."], "negative_caption": ["There are exactly 0 planes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2315587", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315604.jpg", "positive_caption": ["There are exactly 4 sheep in the main pen."], "negative_caption": ["There are exactly 0 sheep in the main pen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2315604", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315705.jpg", "positive_caption": ["There are exactly 4 vehicles in the photo."], "negative_caption": ["There is exactly 1 vehicle in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2315705", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316226.jpg", "positive_caption": ["There are exactly 4 planes."], "negative_caption": ["There are exactly 2 planes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2316226", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317071.jpg", "positive_caption": ["There are exactly 4 airplanes visible in the picture."], "negative_caption": ["There are exactly 0 airplanes visible in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2317071", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317803.jpg", "positive_caption": ["There are exactly 4 elephants."], "negative_caption": ["There are exactly 2 elephants."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2317803", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318073.jpg", "positive_caption": ["There are exactly 4 lights."], "negative_caption": ["There are exactly 3 lights."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2318073", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318842.jpg", "positive_caption": ["There are exactly 8 knobs visible."], "negative_caption": ["There are exactly 3 knobs visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2318842", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319711.jpg", "positive_caption": ["There are exactly 4 tracks."], "negative_caption": ["There are exactly 0 tracks."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2319711", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320007.jpg", "positive_caption": ["There are exactly 4 train tracks."], "negative_caption": ["There are exactly 3 train tracks."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2320007", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320264.jpg", "positive_caption": ["There are exactly 4 different fruits and veggies."], "negative_caption": ["There are exactly 2 different fruits and veggies."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2320264", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321272.jpg", "positive_caption": ["There are exactly 4 accent pillows on the bed."], "negative_caption": ["There are exactly 3 accent pillows on the bed."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2321272", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322395.jpg", "positive_caption": ["There are exactly 4 sheep."], "negative_caption": ["There are exactly 0 sheep."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2322395", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323270.jpg", "positive_caption": ["There are exactly 4 players wearing long pants."], "negative_caption": ["There are exactly 3 players wearing long pants."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2323270", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323770.jpg", "positive_caption": ["There are exactly 5 lemons."], "negative_caption": ["There are exactly 3 lemons."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2323770", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323857.jpg", "positive_caption": ["There are exactly 4 kinds of fruit."], "negative_caption": ["There are exactly 3 kinds of fruit."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2323857", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324078.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2324078", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324256.jpg", "positive_caption": ["There are exactly 4 wheels on the skateboard."], "negative_caption": ["There is exactly 1 wheel on the skateboard."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2324256", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324297.jpg", "positive_caption": ["There are exactly 4 children."], "negative_caption": ["There is exactly 1 child."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2324297", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324638.jpg", "positive_caption": ["There are exactly 4 wheels."], "negative_caption": ["There are exactly 0 wheels."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2324638", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325650.jpg", "positive_caption": ["There are exactly 4 plates in the picture."], "negative_caption": ["There are exactly 3 plates in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2325650", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326133.jpg", "positive_caption": ["You see exactly 4 street lights."], "negative_caption": ["You see exactly 3 street lights."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2326133", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326438.jpg", "positive_caption": ["There are exactly 4."], "negative_caption": ["There are exactly 0."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2326438", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326667.jpg", "positive_caption": ["There are exactly 4 vases."], "negative_caption": ["There are exactly 0 vases."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2326667", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326693.jpg", "positive_caption": ["There are exactly 4 women in the billboard on the left."], "negative_caption": ["There are exactly 0 women in the billboard on the left."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2326693", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498210.jpg", "positive_caption": ["There are exactly 4 men."], "negative_caption": ["There are exactly 2 men."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_498210", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327733.jpg", "positive_caption": ["There are exactly 4 tufts on side of each square cushion."], "negative_caption": ["There are exactly 0 tufts on side of each square cushion."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2327733", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327942.jpg", "positive_caption": ["There are exactly 4 slices of pizza."], "negative_caption": ["There are exactly 3 slices of pizza."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2327942", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328006.jpg", "positive_caption": ["There are exactly 4 large rocks."], "negative_caption": ["There are exactly 0 large rocks."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2328006", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328023.jpg", "positive_caption": ["There are exactly 4 cars parked."], "negative_caption": ["There is exactly 1 car parked."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2328023", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328135.jpg", "positive_caption": ["There are exactly 4 hotdogs shown."], "negative_caption": ["There are exactly 2 hotdogs shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2328135", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328588.jpg", "positive_caption": ["There are exactly 4 oranges."], "negative_caption": ["There are exactly 2 oranges."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2328588", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329328.jpg", "positive_caption": ["There are exactly 4 people in the back seat."], "negative_caption": ["There are exactly 2 people in the back seat."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2329328", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329462.jpg", "positive_caption": ["There are exactly 4 meters."], "negative_caption": ["There is exactly 1 meter."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2329462", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329566.jpg", "positive_caption": ["There are exactly 4 bottles."], "negative_caption": ["There are exactly 0 bottles."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2329566", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330300.jpg", "positive_caption": ["There are exactly 4 lights."], "negative_caption": ["There are exactly 2 lights."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2330300", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330836.jpg", "positive_caption": ["There are exactly 4 wheels on the skateboard."], "negative_caption": ["There are exactly 2 wheels on the skateboard."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2330836", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331238.jpg", "positive_caption": ["There are exactly 4 sheep in the picture."], "negative_caption": ["There are exactly 0 sheep in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2331238", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331862.jpg", "positive_caption": ["They have exactly 4 legs."], "negative_caption": ["They have exactly 2 legs."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2331862", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332306.jpg", "positive_caption": ["There are exactly 4 strings attached to the kite."], "negative_caption": ["There are exactly 3 strings attached to the kite."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2332306", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_497990.jpg", "positive_caption": ["There are exactly 4 tourists."], "negative_caption": ["There are exactly 3 tourists."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_497990", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498020.jpg", "positive_caption": ["There are exactly 5 steps to walk up and enter restaurant."], "negative_caption": ["There is exactly 1 step to walk up and enter restaurant."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_498020", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333096.jpg", "positive_caption": ["There are exactly 4 sets of train tracks in the image."], "negative_caption": ["There are exactly 2 sets of train tracks in the image."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2333096", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498214.jpg", "positive_caption": ["There are exactly 5 guys playing frisbee."], "negative_caption": ["There are exactly 0 guys playing frisbee."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_498214", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333501.jpg", "positive_caption": ["There are exactly 4 cows shown."], "negative_caption": ["There is exactly 1 cow shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2333501", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333820.jpg", "positive_caption": ["There are exactly 4 sheep in the picture."], "negative_caption": ["There is exactly 1 sheep in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2333820", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333990.jpg", "positive_caption": ["There are exactly 4 servings on the plate."], "negative_caption": ["There are exactly 3 servings on the plate."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2333990", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334636.jpg", "positive_caption": ["There are exactly 4 players in this picture."], "negative_caption": ["There are exactly 2 players in this picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2334636", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334719.jpg", "positive_caption": ["There are exactly 4 police bikes."], "negative_caption": ["There are exactly 0 police bikes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2334719", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334898.jpg", "positive_caption": ["There are exactly 4 panes on the window."], "negative_caption": ["There is exactly 1 pane on the window."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2334898", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335225.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2335225", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335757.jpg", "positive_caption": ["There are exactly 4 wine glasses."], "negative_caption": ["There are exactly 0 wine glasses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2335757", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336144.jpg", "positive_caption": ["There are exactly 4 planes."], "negative_caption": ["There are exactly 2 planes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2336144", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336945.jpg", "positive_caption": ["There are exactly 4 fingers visible in the photo."], "negative_caption": ["There is exactly 1 finger visible in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2336945", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337962.jpg", "positive_caption": ["There are exactly 5 players."], "negative_caption": ["There are exactly 3 players."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2337962", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338082.jpg", "positive_caption": ["There are exactly 4 people shown."], "negative_caption": ["There are exactly 0 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2338082", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338295.jpg", "positive_caption": ["There are exactly 4 giraffes in this photo."], "negative_caption": ["There are exactly 3 giraffes in this photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2338295", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338467.jpg", "positive_caption": ["There are exactly 4 windows on the building."], "negative_caption": ["There is exactly 1 window on the building."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2338467", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338787.jpg", "positive_caption": ["There are exactly 9 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2338787", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339051.jpg", "positive_caption": ["There are exactly 4 red buttons."], "negative_caption": ["There are exactly 2 red buttons."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2339051", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339166.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2339166", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339263.jpg", "positive_caption": ["There are exactly 4 horses in the photo."], "negative_caption": ["There is exactly 1 horse in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2339263", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159627.jpg", "positive_caption": ["There are exactly 4 tables."], "negative_caption": ["There is exactly 1 table."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1159627", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339363.jpg", "positive_caption": ["There are exactly 4 skis in the picture."], "negative_caption": ["There are exactly 3 skis in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2339363", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339542.jpg", "positive_caption": ["There are exactly 4 vehicles visible."], "negative_caption": ["There are exactly 2 vehicles visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2339542", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159979.jpg", "positive_caption": ["There are exactly 4 people on the beach."], "negative_caption": ["There are exactly 3 people on the beach."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1159979", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1160207.jpg", "positive_caption": ["There are exactly 5 people in the boat."], "negative_caption": ["There are exactly 0 people in the boat."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1160207", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340774.jpg", "positive_caption": ["There are exactly 4 men."], "negative_caption": ["There are exactly 3 men."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2340774", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340946.jpg", "positive_caption": ["There are exactly 4 coolers."], "negative_caption": ["There are exactly 0 coolers."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2340946", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341071.jpg", "positive_caption": ["There are exactly 4 people standing around the edge of the pool."], "negative_caption": ["There is exactly 1 person standing around the edge of the pool."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2341071", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342832.jpg", "positive_caption": ["There are exactly 4 giraffes."], "negative_caption": ["There are exactly 3 giraffes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342832", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342842.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342842", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342880.jpg", "positive_caption": ["There are exactly 4 people in photo rollerblading."], "negative_caption": ["There is exactly 1 person in photo rollerblading."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342880", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342920.jpg", "positive_caption": ["There are exactly 4 horses shown."], "negative_caption": ["There is exactly 1 horse shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342920", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343499.jpg", "positive_caption": ["There are exactly 4 blue stripes."], "negative_caption": ["There are exactly 0 blue stripes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2343499", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343551.jpg", "positive_caption": ["There are exactly 4 kids playing soccer."], "negative_caption": ["There are exactly 0 kids playing soccer."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2343551", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343770.jpg", "positive_caption": ["There are exactly 4 cars."], "negative_caption": ["There are exactly 2 cars."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2343770", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344186.jpg", "positive_caption": ["There are exactly 4 tents."], "negative_caption": ["There are exactly 2 tents."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344186", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344828.jpg", "positive_caption": ["There are exactly 4 signs in the photo."], "negative_caption": ["There are exactly 0 signs in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344828", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344996.jpg", "positive_caption": ["There are exactly 4 pillows."], "negative_caption": ["There is exactly 1 pillow."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344996", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378774.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2378774", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345114.jpg", "positive_caption": ["Exactly 4 cars can be seen."], "negative_caption": ["Exactly 2 cars can be seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2345114", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345325.jpg", "positive_caption": ["There are exactly 4 surfers in the pic."], "negative_caption": ["There are exactly 3 surfers in the pic."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2345325", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345811.jpg", "positive_caption": ["There are exactly 4 people's faces showing."], "negative_caption": ["There is exactly 1 person's faces showing."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2345811", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345949.jpg", "positive_caption": ["There are exactly 4 planes in the sky."], "negative_caption": ["There are exactly 0 planes in the sky."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2345949", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346078.jpg", "positive_caption": ["There are exactly 6 horses."], "negative_caption": ["There are exactly 0 horses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2346078", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346628.jpg", "positive_caption": ["There are exactly 4 players shown."], "negative_caption": ["There are exactly 3 players shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2346628", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347758.jpg", "positive_caption": ["There are exactly 4 desserts."], "negative_caption": ["There are exactly 0 desserts."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2347758", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347803.jpg", "positive_caption": ["There are exactly 4 workers on the scene."], "negative_caption": ["There are exactly 3 workers on the scene."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2347803", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348430.jpg", "positive_caption": ["There are exactly 4 people on the closest court."], "negative_caption": ["There are exactly 0 people on the closest court."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2348430", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348772.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2348772", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348806.jpg", "positive_caption": ["There are exactly 4 cups."], "negative_caption": ["There are exactly 2 cups."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2348806", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348822.jpg", "positive_caption": ["There are exactly 4 lights on the train front."], "negative_caption": ["There are exactly 0 lights on the train front."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2348822", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349006.jpg", "positive_caption": ["There are exactly 4 lightbulbs."], "negative_caption": ["There are exactly 3 lightbulbs."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2349006", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349621.jpg", "positive_caption": ["There are exactly 5 flowers."], "negative_caption": ["There are exactly 0 flowers."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2349621", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350009.jpg", "positive_caption": ["There are exactly 4 suitcases."], "negative_caption": ["There are exactly 2 suitcases."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2350009", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350818.jpg", "positive_caption": ["There are exactly 4 they."], "negative_caption": ["There are exactly 3 they."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2350818", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351175.jpg", "positive_caption": ["There are exactly 4 bowls shown."], "negative_caption": ["There are exactly 2 bowls shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2351175", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351200.jpg", "positive_caption": ["There are exactly 4 cats shown."], "negative_caption": ["There are exactly 0 cats shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2351200", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352174.jpg", "positive_caption": ["There are exactly 4 people visible."], "negative_caption": ["There are exactly 2 people visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2352174", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353180.jpg", "positive_caption": ["There are exactly 4 gummy bears on the remote."], "negative_caption": ["There are exactly 3 gummy bears on the remote."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2353180", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354169.jpg", "positive_caption": ["There are exactly 4 bikes."], "negative_caption": ["There are exactly 3 bikes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2354169", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354458.jpg", "positive_caption": ["There are exactly 4 vehicles."], "negative_caption": ["There are exactly 2 vehicles."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2354458", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378548.jpg", "positive_caption": ["There are exactly 4 cars."], "negative_caption": ["There are exactly 3 cars."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2378548", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356090.jpg", "positive_caption": ["There are exactly 4 water glasses."], "negative_caption": ["There are exactly 3 water glasses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2356090", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357012.jpg", "positive_caption": ["There are exactly 4 players on the field."], "negative_caption": ["There are exactly 3 players on the field."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2357012", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357020.jpg", "positive_caption": ["There are exactly 4 people shown."], "negative_caption": ["There are exactly 0 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2357020", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357161.jpg", "positive_caption": ["There are exactly 4 animals."], "negative_caption": ["There are exactly 0 animals."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2357161", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358393.jpg", "positive_caption": ["There are exactly 4 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2358393", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358423.jpg", "positive_caption": ["There are exactly 4 people dressed in blue uniforms."], "negative_caption": ["There is exactly 1 person dressed in blue uniforms."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2358423", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362500.jpg", "positive_caption": ["There are exactly 5 black cattle."], "negative_caption": ["There are exactly 3 black cattle."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2362500", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366368.jpg", "positive_caption": ["There are exactly 12 small cups shown."], "negative_caption": ["There is exactly 1 small cup shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2366368", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368047.jpg", "positive_caption": ["There are exactly 8 plants by the fireplace."], "negative_caption": ["There is exactly 1 plant by the fireplace."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2368047", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372063.jpg", "positive_caption": ["There are exactly 9 palm trees."], "negative_caption": ["There are exactly 2 palm trees."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2372063", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373456.jpg", "positive_caption": ["There are exactly 9 muffins pictured."], "negative_caption": ["There are exactly 0 muffins pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2373456", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375581.jpg", "positive_caption": ["There are exactly 6 street signs."], "negative_caption": ["There is exactly 1 street sign."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2375581", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377512.jpg", "positive_caption": ["There are exactly 12 numbers on the clock."], "negative_caption": ["There are exactly 3 numbers on the clock."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2377512", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377550.jpg", "positive_caption": ["There are exactly 5 people standing."], "negative_caption": ["There are exactly 0 people standing."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2377550", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592158.jpg", "positive_caption": ["There are exactly 6 women under the umbrella."], "negative_caption": ["There are exactly 0 women under the umbrella."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592158", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150498.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_150498", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379339.jpg", "positive_caption": ["There are exactly 5 stories to the building."], "negative_caption": ["There is exactly 1 story to the building."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2379339", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592929.jpg", "positive_caption": ["There are exactly 6 visible windows on the top floor of the hosue."], "negative_caption": ["There is exactly 1 visible window on the top floor of the hosue."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592929", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1593082.jpg", "positive_caption": ["There are exactly 12 shelves."], "negative_caption": ["There are exactly 2 shelves."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1593082", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385066.jpg", "positive_caption": ["There are exactly 5 toothbrushes."], "negative_caption": ["There are exactly 0 toothbrushes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2385066", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387338.jpg", "positive_caption": ["There are exactly 5 people pictured."], "negative_caption": ["There are exactly 3 people pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2387338", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389272.jpg", "positive_caption": ["There are exactly 7 cows."], "negative_caption": ["There are exactly 2 cows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2389272", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394242.jpg", "positive_caption": ["There are exactly 7 cows."], "negative_caption": ["There are exactly 3 cows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2394242", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396082.jpg", "positive_caption": ["Exactly 8 windows can be seen on the church."], "negative_caption": ["Exactly 2 windows can be seen on the church."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2396082", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397532.jpg", "positive_caption": ["There are exactly 7 cabinet doors on the top row."], "negative_caption": ["There are exactly 0 cabinet doors on the top row."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2397532", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399167.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2399167", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400586.jpg", "positive_caption": ["There are exactly 21 children."], "negative_caption": ["There is exactly 1 child."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2400586", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401042.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401042", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404184.jpg", "positive_caption": ["There are exactly 7 people on the boat."], "negative_caption": ["There are exactly 3 people on the boat."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2404184", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407094.jpg", "positive_caption": ["There are exactly 10 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2407094", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407966.jpg", "positive_caption": ["There are exactly 9 people in this picture."], "negative_caption": ["There is exactly 1 person in this picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2407966", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316731.jpg", "positive_caption": ["There are exactly 5 bears in the photo."], "negative_caption": ["There are exactly 3 bears in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2316731", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322213.jpg", "positive_caption": ["There are exactly 14 pumpkins."], "negative_caption": ["There are exactly 3 pumpkins."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2322213", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327060.jpg", "positive_caption": ["There are exactly 8 green glasses on the bottom shelf."], "negative_caption": ["There are exactly 2 green glasses on the bottom shelf."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2327060", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327349.jpg", "positive_caption": ["There are exactly 10 soda cans shown."], "negative_caption": ["There are exactly 2 soda cans shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2327349", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327843.jpg", "positive_caption": ["There are exactly 5 bus stops."], "negative_caption": ["There are exactly 3 bus stops."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2327843", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330558.jpg", "positive_caption": ["There are exactly 6 chairs in the photo."], "negative_caption": ["There are exactly 2 chairs in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2330558", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_107913.jpg", "positive_caption": ["There are exactly 8 sticks."], "negative_caption": ["There is exactly 1 stick."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_107913", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338274.jpg", "positive_caption": ["There are exactly 5 animals visible."], "negative_caption": ["There is exactly 1 animal visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2338274", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339046.jpg", "positive_caption": ["There are exactly 5 poles visible."], "negative_caption": ["There are exactly 2 poles visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2339046", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340049.jpg", "positive_caption": ["There are exactly 6 pigeons."], "negative_caption": ["There are exactly 2 pigeons."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2340049", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340418.jpg", "positive_caption": ["There are exactly 5 flowers."], "negative_caption": ["There are exactly 2 flowers."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2340418", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342231.jpg", "positive_caption": ["There are exactly 8 slices shown."], "negative_caption": ["There are exactly 2 slices shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342231", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342667.jpg", "positive_caption": ["There are exactly 5 birds."], "negative_caption": ["There are exactly 3 birds."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342667", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347259.jpg", "positive_caption": ["There are exactly 5 tree trunks visbile."], "negative_caption": ["There are exactly 2 tree trunks visbile."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2347259", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352946.jpg", "positive_caption": ["There are exactly 5 cows."], "negative_caption": ["There is exactly 1 cow."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2352946", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353303.jpg", "positive_caption": ["There are exactly 8 cars."], "negative_caption": ["There are exactly 0 cars."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2353303", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355746.jpg", "positive_caption": ["There are exactly 6 lights in the room."], "negative_caption": ["There are exactly 3 lights in the room."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2355746", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363877.jpg", "positive_caption": ["There are exactly 8 shelves shown."], "negative_caption": ["There are exactly 3 shelves shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2363877", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374366.jpg", "positive_caption": ["There are exactly 6 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2374366", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378613.jpg", "positive_caption": ["There are exactly 9 parachutes in the sky."], "negative_caption": ["There are exactly 3 parachutes in the sky."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2378613", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592677.jpg", "positive_caption": ["There are exactly 5 pizzas on the cookie sheet."], "negative_caption": ["There is exactly 1 pizza on the cookie sheet."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592677", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380707.jpg", "positive_caption": ["There are exactly 13 blue cushions on the floor."], "negative_caption": ["There are exactly 0 blue cushions on the floor."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2380707", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404612.jpg", "positive_caption": ["There are exactly 11 windows visible."], "negative_caption": ["There are exactly 2 windows visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2404612", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316827.jpg", "positive_caption": ["There are exactly 8 windows arched at the top."], "negative_caption": ["There are exactly 0 windows arched at the top."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2316827", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317793.jpg", "positive_caption": ["There are exactly 7 food items on the grill."], "negative_caption": ["There are exactly 2 food items on the grill."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2317793", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318826.jpg", "positive_caption": ["There are exactly 7 elephants shown."], "negative_caption": ["There are exactly 3 elephants shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2318826", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331470.jpg", "positive_caption": ["There are exactly 9 different foods on the plate."], "negative_caption": ["There are exactly 0 different foods on the plate."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2331470", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498131.jpg", "positive_caption": ["There are exactly 5 colors of flowers."], "negative_caption": ["There is exactly 1 color of flowers."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_498131", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591832.jpg", "positive_caption": ["There are exactly 9 lights."], "negative_caption": ["There are exactly 0 lights."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1591832", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344897.jpg", "positive_caption": ["There are exactly 5 people pictured sitting in the stands."], "negative_caption": ["There are exactly 2 people pictured sitting in the stands."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344897", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364822.jpg", "positive_caption": ["There are exactly 10 windows facing the viewer vertical."], "negative_caption": ["There is exactly 1 window facing the viewer vertical."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2364822", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367480.jpg", "positive_caption": ["There are exactly 6 crosses."], "negative_caption": ["There are exactly 3 crosses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2367480", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371565.jpg", "positive_caption": ["There are exactly 5 skis with red on them pictured."], "negative_caption": ["There are exactly 3 skis with red on them pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2371565", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371600.jpg", "positive_caption": ["There are exactly 5 women."], "negative_caption": ["There are exactly 2 women."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2371600", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1160075.jpg", "positive_caption": ["There are exactly 5 people wear sunglasses."], "negative_caption": ["There are exactly 3 people wear sunglasses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1160075", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373987.jpg", "positive_caption": ["There are exactly 8 legs."], "negative_caption": ["There are exactly 0 legs."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2373987", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374510.jpg", "positive_caption": ["There are exactly 8 different items in the picture."], "negative_caption": ["There is exactly 1 different item in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2374510", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150430.jpg", "positive_caption": ["There are exactly 5 wear goggles."], "negative_caption": ["There is exactly 1 wear goggle."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_150430", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592236.jpg", "positive_caption": ["There are exactly 5 chairs in the picture."], "negative_caption": ["There are exactly 0 chairs in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592236", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1593153.jpg", "positive_caption": ["There are exactly 6 trays of pizza on the counter."], "negative_caption": ["There are exactly 0 trays of pizza on the counter."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1593153", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384229.jpg", "positive_caption": ["There are exactly 6 people in the scene."], "negative_caption": ["There are exactly 2 people in the scene."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2384229", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385425.jpg", "positive_caption": ["There are exactly 5 trains in this photo."], "negative_caption": ["There are exactly 2 trains in this photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2385425", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159810.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1159810", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388041.jpg", "positive_caption": ["There are exactly 9 dots between the numbers."], "negative_caption": ["There are exactly 0 dots between the numbers."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2388041", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389077.jpg", "positive_caption": ["There are exactly 5 lights above the mirror."], "negative_caption": ["There are exactly 0 lights above the mirror."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2389077", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390364.jpg", "positive_caption": ["There are exactly 5 objects on the mantle."], "negative_caption": ["There are exactly 2 objects on the mantle."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2390364", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391547.jpg", "positive_caption": ["There are exactly 6 pieces of luggage in the image."], "negative_caption": ["There are exactly 2 pieces of luggage in the image."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2391547", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392254.jpg", "positive_caption": ["There are exactly 6 boats visible in this photo."], "negative_caption": ["There are exactly 3 boats visible in this photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2392254", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395349.jpg", "positive_caption": ["There are exactly 6 chairs around the larger table."], "negative_caption": ["There is exactly 1 chair around the larger table."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2395349", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403382.jpg", "positive_caption": ["There are exactly 14 carrots."], "negative_caption": ["There is exactly 1 carrot."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2403382", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404566.jpg", "positive_caption": ["There are exactly 5 kids in this photo."], "negative_caption": ["There is exactly 1 kid in this photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2404566", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404901.jpg", "positive_caption": ["There are exactly 6 motorcycles in this photo altogether."], "negative_caption": ["There are exactly 0 motorcycles in this photo altogether."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2404901", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406711.jpg", "positive_caption": ["There are exactly 5 flip phones."], "negative_caption": ["There are exactly 0 flip phones."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2406711", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316143.jpg", "positive_caption": ["There are exactly 6 green buttons on the wall."], "negative_caption": ["There are exactly 2 green buttons on the wall."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2316143", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318641.jpg", "positive_caption": ["There are exactly 5 carrots shown."], "negative_caption": ["There is exactly 1 carrot shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2318641", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321028.jpg", "positive_caption": ["There are exactly 12 numbers on the clock."], "negative_caption": ["There are exactly 3 numbers on the clock."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2321028", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335082.jpg", "positive_caption": ["There are exactly 5 pictures on the walls."], "negative_caption": ["There is exactly 1 picture on the walls."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2335082", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335287.jpg", "positive_caption": ["There are exactly 6 building in this picture."], "negative_caption": ["There is exactly 1 building in this picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2335287", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338486.jpg", "positive_caption": ["There are exactly 13 windows in the white building."], "negative_caption": ["There are exactly 2 windows in the white building."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2338486", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342902.jpg", "positive_caption": ["There are exactly 5 people in the image."], "negative_caption": ["There are exactly 2 people in the image."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342902", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342923.jpg", "positive_caption": ["There are exactly 7 letters on the license plate."], "negative_caption": ["There are exactly 0 letters on the license plate."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342923", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150407.jpg", "positive_caption": ["There are exactly 6 onion rings."], "negative_caption": ["There is exactly 1 onion ring."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_150407", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347004.jpg", "positive_caption": ["There are exactly 5 cars attached to engine."], "negative_caption": ["There are exactly 3 cars attached to engine."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2347004", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354541.jpg", "positive_caption": ["There are exactly 6 potatoes on the counter."], "negative_caption": ["There is exactly 1 potato on the counter."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2354541", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355063.jpg", "positive_caption": ["Exactly 6 wheels can be seen."], "negative_caption": ["Exactly 3 wheels can be seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2355063", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356252.jpg", "positive_caption": ["There are exactly 8 legs."], "negative_caption": ["There are exactly 2 legs."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2356252", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356436.jpg", "positive_caption": ["There are exactly 9 pictures on the walls."], "negative_caption": ["There are exactly 3 pictures on the walls."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2356436", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358026.jpg", "positive_caption": ["There are exactly 6 windows shown from the building at the bottom."], "negative_caption": ["There are exactly 2 windows shown from the building at the bottom."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2358026", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359288.jpg", "positive_caption": ["There are exactly 5 people shown in total."], "negative_caption": ["There are exactly 3 people shown in total."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2359288", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361649.jpg", "positive_caption": ["There are exactly 5 birds."], "negative_caption": ["There is exactly 1 bird."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2361649", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364676.jpg", "positive_caption": ["There are exactly 5 tires visible on the closest truck."], "negative_caption": ["There are exactly 2 tires visible on the closest truck."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2364676", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366137.jpg", "positive_caption": ["There are exactly 12 legs in the picture."], "negative_caption": ["There are exactly 2 legs in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2366137", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377144.jpg", "positive_caption": ["There are exactly 6 planes visible."], "negative_caption": ["There are exactly 2 planes visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2377144", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591804.jpg", "positive_caption": ["There are exactly 6 wheels on this display."], "negative_caption": ["There is exactly 1 wheel on this display."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1591804", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591982.jpg", "positive_caption": ["There are exactly 8 pillows total between the two couches."], "negative_caption": ["There are exactly 0 pillows total between the two couches."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1591982", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150406.jpg", "positive_caption": ["Exactly 5 tables can be seen."], "negative_caption": ["Exactly 2 tables can be seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_150406", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592254.jpg", "positive_caption": ["There are exactly 6 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592254", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1593091.jpg", "positive_caption": ["There are exactly 6 chairs."], "negative_caption": ["There is exactly 1 chair."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1593091", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382359.jpg", "positive_caption": ["There are exactly 6 men in the picture."], "negative_caption": ["There are exactly 3 men in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2382359", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392883.jpg", "positive_caption": ["There are exactly 7 traffic lights seen."], "negative_caption": ["There are exactly 3 traffic lights seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2392883", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393661.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2393661", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396059.jpg", "positive_caption": ["There are exactly 18 window panes shown."], "negative_caption": ["There are exactly 0 window panes shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2396059", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408874.jpg", "positive_caption": ["There are exactly 7 spindles on the chair."], "negative_caption": ["There are exactly 0 spindles on the chair."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2408874", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713051.jpg", "positive_caption": ["There are exactly 6 tires on one side of the truck."], "negative_caption": ["There are exactly 2 tires on one side of the truck."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_713051", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713697.jpg", "positive_caption": ["There are exactly 5 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_713697", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417938.jpg", "positive_caption": ["There are exactly 5 bananas shown."], "negative_caption": ["There are exactly 2 bananas shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2417938", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_61593.jpg", "positive_caption": ["There are exactly 14 people at the restaurant."], "negative_caption": ["There is exactly 1 person at the restaurant."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_61593", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315398.jpg", "positive_caption": ["There are exactly 9 donuts in the box."], "negative_caption": ["There are exactly 2 donuts in the box."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2315398", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315601.jpg", "positive_caption": ["There are exactly 6 banana bunches hanging."], "negative_caption": ["There are exactly 2 banana bunches hangings."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2315601", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315685.jpg", "positive_caption": ["There are exactly 6 people in the stands."], "negative_caption": ["There are exactly 0 people in the stands."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2315685", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316256.jpg", "positive_caption": ["There are exactly 9 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2316256", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317393.jpg", "positive_caption": ["There are exactly 5 cherries in the picture."], "negative_caption": ["There are exactly 3 cherries in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2317393", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329503.jpg", "positive_caption": ["There are exactly 12 letters and numbers on the street sign."], "negative_caption": ["There are exactly 2 letters and numbers on the street sign."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2329503", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498244.jpg", "positive_caption": ["There are exactly 7 numbers and letters on the bottom license plate."], "negative_caption": ["There are exactly 3 numbers and letters on the bottom license plate."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_498244", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336300.jpg", "positive_caption": ["There are exactly 5 zebras."], "negative_caption": ["There are exactly 2 zebras."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2336300", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592074.jpg", "positive_caption": ["There are exactly 5 pats of butter in the dish."], "negative_caption": ["There are exactly 2 pats of butter in the dish."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592074", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350629.jpg", "positive_caption": ["There are exactly 5 of the people male."], "negative_caption": ["There are exactly 2 of the people male."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2350629", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351514.jpg", "positive_caption": ["There are exactly 6 people visibly wearing glasses."], "negative_caption": ["There is exactly 1 person visibly wearing glasses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2351514", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352201.jpg", "positive_caption": ["There are exactly 16 rectangles on the garage door."], "negative_caption": ["There are exactly 2 rectangles on the garage door."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2352201", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353138.jpg", "positive_caption": ["There are exactly 6 words total on the sign."], "negative_caption": ["There are exactly 2 words total on the sign."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2353138", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353569.jpg", "positive_caption": ["There are exactly 6 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2353569", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358074.jpg", "positive_caption": ["There are exactly 6 silver cabinet handles at least partially visible."], "negative_caption": ["There is exactly 1 silver cabinet handle at least partially visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2358074", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360501.jpg", "positive_caption": ["Exactly 7 windows can be seen."], "negative_caption": ["Exactly 2 windows can be seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2360501", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362055.jpg", "positive_caption": ["There are exactly 7 men."], "negative_caption": ["There is exactly 1 man."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2362055", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368197.jpg", "positive_caption": ["There are exactly 7 signs."], "negative_caption": ["There are exactly 2 signs."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2368197", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368514.jpg", "positive_caption": ["There are exactly 7 chairs."], "negative_caption": ["There are exactly 3 chairs."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2368514", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370176.jpg", "positive_caption": ["There are exactly 7 horses."], "negative_caption": ["There are exactly 3 horses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2370176", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372280.jpg", "positive_caption": ["There are exactly 7 skis."], "negative_caption": ["There is exactly 1 ski."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2372280", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373297.jpg", "positive_caption": ["There are exactly 7 umbrellas in the picture."], "negative_caption": ["There are exactly 2 umbrellas in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2373297", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374311.jpg", "positive_caption": ["There are exactly 7 lights on the ceiling."], "negative_caption": ["There is exactly 1 light on the ceiling."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2374311", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376065.jpg", "positive_caption": ["There are exactly 6 windows."], "negative_caption": ["There are exactly 0 windows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2376065", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592135.jpg", "positive_caption": ["There are exactly 5 boats on the beach."], "negative_caption": ["There is exactly 1 boat on the beach."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592135", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381619.jpg", "positive_caption": ["There are exactly 7 horses."], "negative_caption": ["There are exactly 2 horses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2381619", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382438.jpg", "positive_caption": ["There are exactly 7 children."], "negative_caption": ["There are exactly 0 children."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2382438", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385400.jpg", "positive_caption": ["There are exactly 7 ties."], "negative_caption": ["There is exactly 1 tie."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2385400", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386290.jpg", "positive_caption": ["There are exactly 7 elephants."], "negative_caption": ["There is exactly 1 elephant."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2386290", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387971.jpg", "positive_caption": ["There are exactly 7 elephants."], "negative_caption": ["There is exactly 1 elephant."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2387971", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391864.jpg", "positive_caption": ["There are exactly 7 seats pictured behind the bench."], "negative_caption": ["There are exactly 2 seats pictured behind the bench."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2391864", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393147.jpg", "positive_caption": ["There are exactly 7 people in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2393147", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402103.jpg", "positive_caption": ["There are exactly 7 people in the center canoe."], "negative_caption": ["There are exactly 3 people in the center canoe."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2402103", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407637.jpg", "positive_caption": ["There are exactly 7 white stripes on the street."], "negative_caption": ["There are exactly 3 white stripes on the street."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2407637", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409923.jpg", "positive_caption": ["There are exactly 7 people in the room."], "negative_caption": ["There is exactly 1 person in the room."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2409923", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413823.jpg", "positive_caption": ["There are exactly 7 buses."], "negative_caption": ["There are exactly 3 buses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2413823", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415100.jpg", "positive_caption": ["There are exactly 7 yellow stripes on the street."], "negative_caption": ["There are exactly 2 yellow stripes on the street."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2415100", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_712986.jpg", "positive_caption": ["There are exactly 7 signs around the clock tower."], "negative_caption": ["There are exactly 0 signs around the clock tower."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_712986", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417023.jpg", "positive_caption": ["There are exactly 7 raspberries pictured."], "negative_caption": ["There is exactly 1 raspberry pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2417023", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319372.jpg", "positive_caption": ["There are exactly 8 hats visible."], "negative_caption": ["There are exactly 3 hats visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2319372", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319378.jpg", "positive_caption": ["There are exactly 7 people present."], "negative_caption": ["There are exactly 0 people present."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2319378", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327689.jpg", "positive_caption": ["There are exactly 7 animals by the fence."], "negative_caption": ["There are exactly 0 animals by the fence."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2327689", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330058.jpg", "positive_caption": ["There are exactly 7 giraffes in the picture."], "negative_caption": ["There are exactly 2 giraffes in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2330058", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332401.jpg", "positive_caption": ["There are exactly 7 garlic."], "negative_caption": ["There are exactly 2 garlic."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2332401", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334682.jpg", "positive_caption": ["There are exactly 7 cars in the photo."], "negative_caption": ["There are exactly 3 cars in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2334682", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335146.jpg", "positive_caption": ["There are exactly 7 sheep."], "negative_caption": ["There is exactly 1 sheep."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2335146", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336637.jpg", "positive_caption": ["There are exactly 7 planes in the photo."], "negative_caption": ["There are exactly 2 planes in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2336637", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340658.jpg", "positive_caption": ["There are exactly 7 kites flying."], "negative_caption": ["There are exactly 3 kites flying."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2340658", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350104.jpg", "positive_caption": ["There are exactly 7 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2350104", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355494.jpg", "positive_caption": ["There are exactly 7 train cars."], "negative_caption": ["There are exactly 0 train cars."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2355494", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355921.jpg", "positive_caption": ["There are exactly 7 traffic lights red."], "negative_caption": ["There are exactly 3 traffic lights red."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2355921", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370691.jpg", "positive_caption": ["There are exactly 14 umbrellas pictured here."], "negative_caption": ["There are exactly 0 umbrellas pictured here."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2370691", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376329.jpg", "positive_caption": ["There are exactly 6 yellow flowers."], "negative_caption": ["There are exactly 0 yellow flowers."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2376329", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392692.jpg", "positive_caption": ["There are exactly 14 people featured."], "negative_caption": ["There are exactly 3 people featured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2392692", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401072.jpg", "positive_caption": ["There are exactly 14 donuts displayed."], "negative_caption": ["There are exactly 3 donuts displayed."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401072", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404437.jpg", "positive_caption": ["There are exactly 14 umbrellas in the picture."], "negative_caption": ["There are exactly 3 umbrellas in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2404437", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339033.jpg", "positive_caption": ["There are exactly 14 cupcakes."], "negative_caption": ["There are exactly 2 cupcakes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2339033", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340891.jpg", "positive_caption": ["There are exactly 14 people pictured."], "negative_caption": ["There is exactly 1 person pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2340891", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361004.jpg", "positive_caption": ["There are exactly 5 players."], "negative_caption": ["There are exactly 0 players."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2361004", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362736.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2362736", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364780.jpg", "positive_caption": ["There are exactly 5 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2364780", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365133.jpg", "positive_caption": ["There are exactly 5 people in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2365133", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365159.jpg", "positive_caption": ["There are exactly 6 animals in the picture."], "negative_caption": ["There are exactly 2 animals in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2365159", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367404.jpg", "positive_caption": ["There are exactly 5 birds."], "negative_caption": ["There are exactly 2 birds."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2367404", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367641.jpg", "positive_caption": ["There are exactly 5 people at least partially visible."], "negative_caption": ["There is exactly 1 person at least partially visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2367641", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369498.jpg", "positive_caption": ["There are exactly 5 birds above the water."], "negative_caption": ["There are exactly 0 birds above the water."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2369498", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370037.jpg", "positive_caption": ["There are exactly 5 bears."], "negative_caption": ["There is exactly 1 bear."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2370037", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370512.jpg", "positive_caption": ["There are exactly 5 people in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2370512", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371409.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2371409", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371843.jpg", "positive_caption": ["There are exactly 5 players."], "negative_caption": ["There are exactly 0 players."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2371843", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372081.jpg", "positive_caption": ["There are exactly 5 jars pictured."], "negative_caption": ["There are exactly 2 jars pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2372081", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372332.jpg", "positive_caption": ["There are exactly 5 people in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2372332", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373129.jpg", "positive_caption": ["Exactly 5 people can be seen."], "negative_caption": ["Exactly 3 people can be seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2373129", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374520.jpg", "positive_caption": ["There are exactly 5 people at the table."], "negative_caption": ["There are exactly 3 people at the table."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2374520", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374787.jpg", "positive_caption": ["There are exactly 5 umbrellas shown."], "negative_caption": ["There are exactly 0 umbrellas shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2374787", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377383.jpg", "positive_caption": ["There are exactly 5 ducks."], "negative_caption": ["There are exactly 0 ducks."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2377383", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150527.jpg", "positive_caption": ["There are exactly 15 cows."], "negative_caption": ["There are exactly 2 cows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_150527", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382056.jpg", "positive_caption": ["There are exactly 5 buses."], "negative_caption": ["There is exactly 1 bus."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2382056", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382317.jpg", "positive_caption": ["There are exactly 5 children."], "negative_caption": ["There is exactly 1 child."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2382317", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382402.jpg", "positive_caption": ["The polar bear has exactly 5 toes on his foot."], "negative_caption": ["The polar bear has exactly 0 toes on his foot."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2382402", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382902.jpg", "positive_caption": ["There are exactly 5 light posts."], "negative_caption": ["There are exactly 0 light posts."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2382902", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383358.jpg", "positive_caption": ["There are exactly 5 men."], "negative_caption": ["There are exactly 0 men."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2383358", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384064.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2384064", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386897.jpg", "positive_caption": ["There are exactly 5 crosses on the building."], "negative_caption": ["There are exactly 0 crosses on the building."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2386897", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387273.jpg", "positive_caption": ["There are exactly 5 people shown."], "negative_caption": ["There are exactly 0 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2387273", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388924.jpg", "positive_caption": ["There are exactly 5 white birds."], "negative_caption": ["There are exactly 3 white birds."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2388924", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389969.jpg", "positive_caption": ["There are exactly 5 wax figures in the picture."], "negative_caption": ["There are exactly 2 wax figures in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2389969", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390572.jpg", "positive_caption": ["There are exactly 5 people pictured."], "negative_caption": ["There are exactly 0 people pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2390572", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391470.jpg", "positive_caption": ["There are exactly 5 umbrellas open."], "negative_caption": ["There are exactly 0 umbrellas open."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2391470", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393648.jpg", "positive_caption": ["There are exactly 5 laptops visible."], "negative_caption": ["There is exactly 1 laptop visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2393648", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394146.jpg", "positive_caption": ["There are exactly 5 people shown."], "negative_caption": ["There are exactly 2 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2394146", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394458.jpg", "positive_caption": ["There are exactly 5 people in the scene."], "negative_caption": ["There is exactly 1 person in the scene."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2394458", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396353.jpg", "positive_caption": ["There are exactly 5 men in the photo."], "negative_caption": ["There is exactly 1 man in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2396353", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398292.jpg", "positive_caption": ["There are exactly 5 sheep in the pasture."], "negative_caption": ["There are exactly 2 sheep in the pasture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2398292", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401034.jpg", "positive_caption": ["There are exactly 5 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401034", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402688.jpg", "positive_caption": ["There are exactly 5 flower buds."], "negative_caption": ["There are exactly 2 flower buds."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2402688", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403512.jpg", "positive_caption": ["There are exactly 5 people visible."], "negative_caption": ["There are exactly 2 people visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2403512", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404018.jpg", "positive_caption": ["There are exactly 5 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2404018", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405539.jpg", "positive_caption": ["There are exactly 5 zebras in the photo."], "negative_caption": ["There are exactly 3 zebras in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2405539", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405921.jpg", "positive_caption": ["Exactly 5 hot dogs have cheese on them."], "negative_caption": ["Exactly 3 hot dogs have cheese on them."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2405921", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407396.jpg", "positive_caption": ["There are exactly 5 berries."], "negative_caption": ["There is exactly 1 berry."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2407396", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408245.jpg", "positive_caption": ["You see exactly 5 Bats on her hat."], "negative_caption": ["You see exactly 3 Bats on her hat."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2408245", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409479.jpg", "positive_caption": ["Exactly 5 vases can be seen."], "negative_caption": ["Exactly 3 vases can be seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2409479", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409749.jpg", "positive_caption": ["There are exactly 5 giraffes in the picture."], "negative_caption": ["There are exactly 2 giraffes in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2409749", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409877.jpg", "positive_caption": ["There are exactly 5 bikes pictured."], "negative_caption": ["There are exactly 0 bikes pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2409877", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410209.jpg", "positive_caption": ["There are exactly 5 animals visible."], "negative_caption": ["There are exactly 3 animals visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2410209", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410496.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2410496", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411689.jpg", "positive_caption": ["There are exactly 5 structures in the picture."], "negative_caption": ["There are exactly 0 structures in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2411689", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412019.jpg", "positive_caption": ["There are exactly 5 sun pictures across the skirt of the settee."], "negative_caption": ["There are exactly 3 sun pictures across the skirt of the settee."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2412019", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412097.jpg", "positive_caption": ["There are exactly 5 sheep."], "negative_caption": ["There are exactly 3 sheep."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2412097", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413482.jpg", "positive_caption": ["You see exactly 5 teeth on the child."], "negative_caption": ["You see exactly 0 teeth on the child."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2413482", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413980.jpg", "positive_caption": ["There are exactly 5 women in the picture."], "negative_caption": ["There are exactly 2 women in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2413980", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415273.jpg", "positive_caption": ["There are exactly 5 men in the photo."], "negative_caption": ["There are exactly 0 men in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2415273", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416630.jpg", "positive_caption": ["There are exactly 5 images of the men displayed."], "negative_caption": ["There are exactly 3 images of the men displayed."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2416630", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416865.jpg", "positive_caption": ["There are exactly 5 black sheep shown."], "negative_caption": ["There is exactly 1 black sheep shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2416865", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713280.jpg", "positive_caption": ["There are exactly 5 large pots."], "negative_caption": ["There are exactly 2 large pots."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_713280", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316217.jpg", "positive_caption": ["There are exactly 6 logs on the bottom row."], "negative_caption": ["There are exactly 2 logs on the bottom row."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2316217", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319922.jpg", "positive_caption": ["There are exactly 5 people sitting in the front row."], "negative_caption": ["There is exactly 1 person sitting in the front row."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2319922", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320102.jpg", "positive_caption": ["There are exactly 5 dogs."], "negative_caption": ["There are exactly 3 dogs."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2320102", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320226.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2320226", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325142.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2325142", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326730.jpg", "positive_caption": ["There are exactly 5 people shown."], "negative_caption": ["There are exactly 2 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2326730", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327539.jpg", "positive_caption": ["There are exactly 5 toothbrushes in the photo."], "negative_caption": ["There is exactly 1 toothbrush in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2327539", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328442.jpg", "positive_caption": ["There are exactly 5 teddy bears in the picture."], "negative_caption": ["There are exactly 3 teddy bears in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2328442", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328805.jpg", "positive_caption": ["There are exactly 5 trucks visible."], "negative_caption": ["There are exactly 0 trucks visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2328805", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331656.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2331656", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334375.jpg", "positive_caption": ["There are exactly 5 green lights on computer."], "negative_caption": ["There are exactly 2 green lights on computer."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2334375", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334657.jpg", "positive_caption": ["There are exactly 5 train cars."], "negative_caption": ["There are exactly 2 train cars."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2334657", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336401.jpg", "positive_caption": ["There are exactly 5 onion slices in the photo."], "negative_caption": ["There are exactly 2 onion slices in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2336401", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336506.jpg", "positive_caption": ["There are exactly 5 people shown."], "negative_caption": ["There are exactly 0 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2336506", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336927.jpg", "positive_caption": ["There are exactly 5 people shown in the water."], "negative_caption": ["There are exactly 3 people shown in the water."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2336927", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339400.jpg", "positive_caption": ["There are exactly 5 sheep shown."], "negative_caption": ["There are exactly 0 sheep shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2339400", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159800.jpg", "positive_caption": ["There are exactly 5 people on the boat."], "negative_caption": ["There is exactly 1 person on the boat."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1159800", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340051.jpg", "positive_caption": ["There are exactly 5 doors."], "negative_caption": ["There are exactly 3 doors."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2340051", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340393.jpg", "positive_caption": ["There are exactly 5 surfboards shown."], "negative_caption": ["There is exactly 1 surfboard shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2340393", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341856.jpg", "positive_caption": ["There are exactly 5 sheep."], "negative_caption": ["There are exactly 2 sheep."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2341856", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343323.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2343323", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343550.jpg", "positive_caption": ["There are exactly 5 arrows in the picture."], "negative_caption": ["There are exactly 3 arrows in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2343550", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344908.jpg", "positive_caption": ["There are exactly 5 sheep."], "negative_caption": ["There are exactly 0 sheep."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344908", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344977.jpg", "positive_caption": ["There are exactly 5 blue honey bears."], "negative_caption": ["There are exactly 3 blue honey bears."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344977", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345651.jpg", "positive_caption": ["There are exactly 11 thin rings appear on the vase."], "negative_caption": ["There are exactly 0 thin rings appear on the vase."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2345651", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346499.jpg", "positive_caption": ["There are exactly 5 women in front of the table."], "negative_caption": ["There is exactly 1 woman in front of the table."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2346499", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346768.jpg", "positive_caption": ["There are exactly 5 signs."], "negative_caption": ["There are exactly 2 signs."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2346768", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347048.jpg", "positive_caption": ["There are exactly 5 croutons on the salad."], "negative_caption": ["There are exactly 3 croutons on the salad."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2347048", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347241.jpg", "positive_caption": ["There are exactly 5 pizzas."], "negative_caption": ["There are exactly 2 pizzas."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2347241", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349020.jpg", "positive_caption": ["There are exactly 5 people shown."], "negative_caption": ["There are exactly 3 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2349020", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350791.jpg", "positive_caption": ["There are exactly 5 elephants shown."], "negative_caption": ["There is exactly 1 elephant shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2350791", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351393.jpg", "positive_caption": ["There are exactly 5 kites flying in the air."], "negative_caption": ["There is exactly 1 kite flying in the air."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2351393", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352855.jpg", "positive_caption": ["There are exactly 5 carts."], "negative_caption": ["There are exactly 0 carts."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2352855", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353525.jpg", "positive_caption": ["There are exactly 5 couches shown here."], "negative_caption": ["There is exactly 1 couch shown here."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2353525", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354376.jpg", "positive_caption": ["There are exactly 5 giraffes."], "negative_caption": ["There are exactly 3 giraffes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2354376", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354734.jpg", "positive_caption": ["There are exactly 5 people dining at the table."], "negative_caption": ["There are exactly 3 people dining at the table."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2354734", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357138.jpg", "positive_caption": ["There are exactly 5 lemon slices."], "negative_caption": ["There are exactly 3 lemon slices."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2357138", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357147.jpg", "positive_caption": ["You see exactly 5 yellow stripes."], "negative_caption": ["You see exactly 1 yellow stripe."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2357147", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358654.jpg", "positive_caption": ["You see exactly 5 toes."], "negative_caption": ["You see exactly 2 toes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2358654", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358800.jpg", "positive_caption": ["There are exactly 5 people shown."], "negative_caption": ["There are exactly 0 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2358800", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361742.jpg", "positive_caption": ["There are exactly 8 boats."], "negative_caption": ["There are exactly 3 boats."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2361742", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365048.jpg", "positive_caption": ["There are exactly 8 people in this room."], "negative_caption": ["There is exactly 1 person in this room."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2365048", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367399.jpg", "positive_caption": ["There are exactly 8 horses."], "negative_caption": ["There are exactly 0 horses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2367399", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369141.jpg", "positive_caption": ["There are exactly 8 doughnuts."], "negative_caption": ["There is exactly 1 doughnut."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2369141", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591862.jpg", "positive_caption": ["There are exactly 8 empty bowls visible."], "negative_caption": ["There is exactly 1 empty bowl visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1591862", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381009.jpg", "positive_caption": ["There are exactly 8 Numbers on the sign."], "negative_caption": ["There are exactly 3 Numbers on the sign."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2381009", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383336.jpg", "positive_caption": ["There are exactly 8 donuts on the first plate."], "negative_caption": ["There are exactly 2 donuts on the first plate."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2383336", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385765.jpg", "positive_caption": ["There are exactly 8 stairs visible."], "negative_caption": ["There are exactly 0 stairs visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2385765", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395433.jpg", "positive_caption": ["There are exactly 8 books pictured."], "negative_caption": ["There are exactly 2 books pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2395433", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401147.jpg", "positive_caption": ["There are exactly 8 sheep."], "negative_caption": ["There are exactly 3 sheep."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401147", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401721.jpg", "positive_caption": ["There are exactly 8 slices."], "negative_caption": ["There is exactly 1 slice."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401721", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403566.jpg", "positive_caption": ["There are exactly 8 kites in the sky."], "negative_caption": ["There are exactly 3 kites in the sky."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2403566", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407007.jpg", "positive_caption": ["There are exactly 8 windows."], "negative_caption": ["There are exactly 0 windows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2407007", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407693.jpg", "positive_caption": ["There are exactly 8 giraffes."], "negative_caption": ["There are exactly 2 giraffes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2407693", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407788.jpg", "positive_caption": ["There are exactly 8 slices of pizza."], "negative_caption": ["There are exactly 2 slices of pizza."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2407788", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409712.jpg", "positive_caption": ["There are exactly 8 kites visible in the sky."], "negative_caption": ["There are exactly 2 kites visible in the sky."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2409712", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411251.jpg", "positive_caption": ["There are exactly 8 sinks."], "negative_caption": ["There are exactly 0 sinks."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2411251", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414892.jpg", "positive_caption": ["There are exactly 8 slices of pizza."], "negative_caption": ["There are exactly 3 slices of pizza."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2414892", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415103.jpg", "positive_caption": ["There are exactly 8 people were in the picture."], "negative_caption": ["There are exactly 0 people were in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2415103", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415318.jpg", "positive_caption": ["There are exactly 6 bikes."], "negative_caption": ["There are exactly 0 bikes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2415318", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315985.jpg", "positive_caption": ["There are exactly 8 vehicles on the street."], "negative_caption": ["There are exactly 0 vehicles on the street."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2315985", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316291.jpg", "positive_caption": ["There are exactly 8 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2316291", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319783.jpg", "positive_caption": ["There are exactly 8 traffic lights in the picture."], "negative_caption": ["There are exactly 0 traffic lights in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2319783", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324760.jpg", "positive_caption": ["There are exactly 8 horses."], "negative_caption": ["There are exactly 2 horses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2324760", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332684.jpg", "positive_caption": ["There are exactly 8 chairs at the dining table."], "negative_caption": ["There are exactly 0 chairs at the dining table."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2332684", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335334.jpg", "positive_caption": ["There are exactly 11 people clearly visible."], "negative_caption": ["There are exactly 0 people clearly visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2335334", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337409.jpg", "positive_caption": ["There are exactly 8 slices of pizza."], "negative_caption": ["There are exactly 2 slices of pizza."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2337409", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159414.jpg", "positive_caption": ["There are exactly 8 lamps."], "negative_caption": ["There are exactly 0 lamps."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1159414", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340278.jpg", "positive_caption": ["There are exactly 8 vehicles shown."], "negative_caption": ["There are exactly 2 vehicles shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2340278", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342316.jpg", "positive_caption": ["There are exactly 8 red letters."], "negative_caption": ["There are exactly 0 red letters."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342316", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344000.jpg", "positive_caption": ["There are exactly 8 light poles."], "negative_caption": ["There are exactly 0 light poles."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344000", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344511.jpg", "positive_caption": ["There are exactly 8 food items here."], "negative_caption": ["There are exactly 3 food items here."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344511", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347382.jpg", "positive_caption": ["There are exactly 8 things outside of the purse."], "negative_caption": ["There are exactly 3 things outside of the purse."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2347382", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347700.jpg", "positive_caption": ["There are exactly 8 slices."], "negative_caption": ["There are exactly 2 slices."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2347700", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362052.jpg", "positive_caption": ["There are exactly 9 squares on the window."], "negative_caption": ["There are exactly 0 squares on the window."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2362052", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370834.jpg", "positive_caption": ["There are exactly 9 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2370834", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592586.jpg", "positive_caption": ["There are exactly 9 people in this picture."], "negative_caption": ["There are exactly 2 people in this picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592586", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592658.jpg", "positive_caption": ["There are exactly 9 mirrors on the lawn."], "negative_caption": ["There are exactly 2 mirrors on the lawn."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592658", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381349.jpg", "positive_caption": ["There are exactly 9 flowers."], "negative_caption": ["There are exactly 2 flowers."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2381349", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285946.jpg", "positive_caption": ["There are exactly 10 pineapples."], "negative_caption": ["There are exactly 3 pineapples."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_285946", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389920.jpg", "positive_caption": ["There are exactly 9 people shown."], "negative_caption": ["There are exactly 3 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2389920", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406898.jpg", "positive_caption": ["There are exactly 9 horses."], "negative_caption": ["There are exactly 2 horses."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2406898", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316187.jpg", "positive_caption": ["There are exactly 9 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2316187", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317251.jpg", "positive_caption": ["There are exactly 9 people shown."], "negative_caption": ["There is exactly 1 person shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2317251", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337379.jpg", "positive_caption": ["There are exactly 9 men."], "negative_caption": ["There are exactly 2 men."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2337379", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347404.jpg", "positive_caption": ["There are exactly 9 people shown."], "negative_caption": ["There are exactly 3 people shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2347404", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348273.jpg", "positive_caption": ["There are exactly 9 items in there."], "negative_caption": ["There are exactly 1 items in there."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2348273", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356935.jpg", "positive_caption": ["There are exactly 9 flowers."], "negative_caption": ["There is exactly 1 flower."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2356935", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358515.jpg", "positive_caption": ["There are exactly 9 motorcycles."], "negative_caption": ["There are exactly 0 motorcycles."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2358515", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363341.jpg", "positive_caption": ["There are exactly 6 pizzas."], "negative_caption": ["There are exactly 2 pizzas."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2363341", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365245.jpg", "positive_caption": ["There are exactly 6 cows in the picture."], "negative_caption": ["There is exactly 1 cow in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2365245", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368860.jpg", "positive_caption": ["There are exactly 6 players on the field."], "negative_caption": ["There are exactly 2 players on the field."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2368860", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369629.jpg", "positive_caption": ["There are exactly 6 items on the black bar."], "negative_caption": ["There are exactly 0 items on the black bar."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2369629", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374843.jpg", "positive_caption": ["There are exactly 6 umbrellas."], "negative_caption": ["There are exactly 3 umbrellas."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2374843", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375204.jpg", "positive_caption": ["There are exactly 6 statues shown."], "negative_caption": ["There are exactly 3 statues shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2375204", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377266.jpg", "positive_caption": ["There are exactly 6 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2377266", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377477.jpg", "positive_caption": ["There are exactly 6 chairs."], "negative_caption": ["There is exactly 1 chair."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2377477", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592422.jpg", "positive_caption": ["There are exactly 6 lights lining the building."], "negative_caption": ["There is exactly 1 light lining the building."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592422", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379158.jpg", "positive_caption": ["There are exactly 6 lights on the front of the train."], "negative_caption": ["There are exactly 0 lights on the front of the train."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2379158", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592881.jpg", "positive_caption": ["There are exactly 6 blue arrows on the sign."], "negative_caption": ["There are exactly 3 blue arrows on the sign."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1592881", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381615.jpg", "positive_caption": ["There are exactly 6 players shown."], "negative_caption": ["There are exactly 2 players shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2381615", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381861.jpg", "positive_caption": ["There are exactly 6 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2381861", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382392.jpg", "positive_caption": ["There are exactly 6 spoons attached to the toaster."], "negative_caption": ["There are exactly 0 spoons attached to the toaster."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2382392", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387506.jpg", "positive_caption": ["There are exactly 6 treats pictured."], "negative_caption": ["There are exactly 3 treats pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2387506", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388191.jpg", "positive_caption": ["There are exactly 6 knobs on the stove."], "negative_caption": ["There are exactly 0 knobs on the stove."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2388191", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389355.jpg", "positive_caption": ["There are exactly 6 teddy bears."], "negative_caption": ["There is exactly 1 teddy bear."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2389355", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390433.jpg", "positive_caption": ["There are exactly 6 players shown."], "negative_caption": ["There is exactly 1 player shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2390433", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390830.jpg", "positive_caption": ["There are exactly 6 whole pastries shown."], "negative_caption": ["There are exactly 3 whole pastries shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2390830", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390919.jpg", "positive_caption": ["There are exactly 6 olives on the pizza."], "negative_caption": ["There are exactly 2 olives on the pizza."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2390919", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391234.jpg", "positive_caption": ["There are exactly 6 umbrellas."], "negative_caption": ["There are exactly 2 umbrellas."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2391234", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394614.jpg", "positive_caption": ["There are exactly 6 cabinet doors shown at the top of the photo."], "negative_caption": ["There are exactly 2 cabinet doors shown at the top of the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2394614", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394634.jpg", "positive_caption": ["There are exactly 6 people in both pictures."], "negative_caption": ["There is exactly 1 person in both pictures."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2394634", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394907.jpg", "positive_caption": ["There are exactly 11 cups on the table."], "negative_caption": ["There are exactly 0 cups on the table."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2394907", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395590.jpg", "positive_caption": ["There are exactly 6 pillows."], "negative_caption": ["There are exactly 3 pillows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2395590", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397330.jpg", "positive_caption": ["There are exactly 6 pieces of pizza."], "negative_caption": ["There are exactly 3 pieces of pizza."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2397330", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399358.jpg", "positive_caption": ["There are exactly 6 tomatoes."], "negative_caption": ["There are exactly 0 tomatoes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2399358", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400175.jpg", "positive_caption": ["There are exactly 6 spectators in the photo."], "negative_caption": ["There are exactly 2 spectators in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2400175", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400372.jpg", "positive_caption": ["There are exactly 6 chairs in the image."], "negative_caption": ["There are exactly 3 chairs in the image."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2400372", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400778.jpg", "positive_caption": ["Exactly 6 giraffes can be seen."], "negative_caption": ["Exactly 0 giraffes can be seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2400778", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401934.jpg", "positive_caption": ["There are exactly 6 buildings."], "negative_caption": ["There is exactly 1 building."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401934", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403198.jpg", "positive_caption": ["There are exactly 6 male pictured."], "negative_caption": ["There are exactly 2 males pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2403198", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403589.jpg", "positive_caption": ["There are exactly 6 candles on the cake."], "negative_caption": ["There is exactly 1 candle on the cake."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2403589", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403679.jpg", "positive_caption": ["There are exactly 6 cell phones on the red tray."], "negative_caption": ["There are exactly 3 cell phones on the red tray."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2403679", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405038.jpg", "positive_caption": ["There are exactly 6 goats."], "negative_caption": ["There are exactly 2 goats."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2405038", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406505.jpg", "positive_caption": ["There are exactly 6 people in the water."], "negative_caption": ["There are exactly 2 people in the water."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2406505", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408513.jpg", "positive_caption": ["There are exactly 6 horses."], "negative_caption": ["There is exactly 1 horse."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2408513", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409065.jpg", "positive_caption": ["You see exactly 6 legs."], "negative_caption": ["You see exactly 1 leg."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2409065", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413285.jpg", "positive_caption": ["There are exactly 6 remotes."], "negative_caption": ["There are exactly 2 remotes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2413285", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415767.jpg", "positive_caption": ["There are exactly 6 skaters pictured."], "negative_caption": ["There is exactly 1 skater pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2415767", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713172.jpg", "positive_caption": ["There are exactly 6 different tracks may this train take."], "negative_caption": ["There is exactly 1 different track may this train take."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_713172", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498021.jpg", "positive_caption": ["There are exactly 6 men skiing."], "negative_caption": ["There are exactly 3 men skiing."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_498021", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713782.jpg", "positive_caption": ["There are exactly 6 ribbons displayed."], "negative_caption": ["There are exactly 2 ribbons displayed."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_713782", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315553.jpg", "positive_caption": ["There are exactly 6 zebras."], "negative_caption": ["There are exactly 2 zebras."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2315553", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316697.jpg", "positive_caption": ["There are exactly 6 planes flying."], "negative_caption": ["There are exactly 0 planes flying."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2316697", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318640.jpg", "positive_caption": ["There are exactly 6 green leaves on the pizza."], "negative_caption": ["There are exactly 3 green leaves on the pizza."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2318640", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320273.jpg", "positive_caption": ["There are exactly 6 umbrellas in the picture."], "negative_caption": ["There are exactly 0 umbrellas in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2320273", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320735.jpg", "positive_caption": ["There are exactly 6 windows on the small brick building."], "negative_caption": ["There are exactly 0 windows on the small brick building."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2320735", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322101.jpg", "positive_caption": ["There are exactly 6 giraffe in the picture."], "negative_caption": ["There are exactly 2 giraffes in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2322101", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322813.jpg", "positive_caption": ["There are exactly 6 horses."], "negative_caption": ["There is exactly 1 horse."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2322813", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324837.jpg", "positive_caption": ["There are exactly 6 cameras in the window."], "negative_caption": ["There are exactly 2 cameras in the window."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2324837", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325735.jpg", "positive_caption": ["There are exactly 6 buildings visible."], "negative_caption": ["There are exactly 3 buildings visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2325735", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326004.jpg", "positive_caption": ["There are exactly 6 pillows."], "negative_caption": ["There are exactly 0 pillows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2326004", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328541.jpg", "positive_caption": ["There are exactly 6 men standing."], "negative_caption": ["There is exactly 1 man standing."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2328541", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330359.jpg", "positive_caption": ["There are exactly 6 benches on this road."], "negative_caption": ["There are exactly 0 benches on this road."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2330359", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331325.jpg", "positive_caption": ["There are exactly 6 tracks."], "negative_caption": ["There is exactly 1 track."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2331325", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331474.jpg", "positive_caption": ["There are exactly 6 people in this picture."], "negative_caption": ["There are exactly 2 people in this picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2331474", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332821.jpg", "positive_caption": ["There are exactly 6 signs."], "negative_caption": ["There is exactly 1 sign."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2332821", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335163.jpg", "positive_caption": ["Exactly 6 people have umbrellas."], "negative_caption": ["Exactly 3 people have umbrellas."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2335163", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337724.jpg", "positive_caption": ["There are exactly 6 giraffes."], "negative_caption": ["There is exactly 1 giraffe."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2337724", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337790.jpg", "positive_caption": ["There are exactly 6 lights."], "negative_caption": ["There are exactly 3 lights."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2337790", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338716.jpg", "positive_caption": ["There are exactly 6 people in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2338716", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159542.jpg", "positive_caption": ["There are exactly 6 lightbulbs on the clock."], "negative_caption": ["There is exactly 1 lightbulb on the clock."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1159542", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339254.jpg", "positive_caption": ["There are exactly 6 kids."], "negative_caption": ["There are exactly 0 kids."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2339254", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343079.jpg", "positive_caption": ["There are exactly 6 animals pictured."], "negative_caption": ["There is exactly 1 animal pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2343079", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345121.jpg", "positive_caption": ["There are exactly 6 different vegetables."], "negative_caption": ["There are exactly 2 different vegetables."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2345121", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345853.jpg", "positive_caption": ["There are exactly 6 umbrellas in this picture."], "negative_caption": ["There are exactly 3 umbrellas in this picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2345853", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345927.jpg", "positive_caption": ["There are exactly 6 zebras in this picture."], "negative_caption": ["There are exactly 3 zebras in this picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2345927", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348503.jpg", "positive_caption": ["There are exactly 6 players in the photo."], "negative_caption": ["There are exactly 3 players in the photo."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2348503", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348566.jpg", "positive_caption": ["There are exactly 6 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2348566", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350013.jpg", "positive_caption": ["There are exactly 6 umbrellas pictured."], "negative_caption": ["There are exactly 3 umbrellas pictured."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2350013", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358386.jpg", "positive_caption": ["There are exactly 6 slices left."], "negative_caption": ["There is exactly 1 slice left."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2358386", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363538.jpg", "positive_caption": ["There are exactly 19 banana slices."], "negative_caption": ["There are exactly 0 banana slices."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2363538", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350321.jpg", "positive_caption": ["There are exactly 19 seeds in this picture."], "negative_caption": ["There are exactly 2 seeds in this picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2350321", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363884.jpg", "positive_caption": ["There are exactly 11 carrots."], "negative_caption": ["There are exactly 3 carrots."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2363884", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396151.jpg", "positive_caption": ["There are exactly 11 glass bottles in the image."], "negative_caption": ["There is exactly 1 glass bottle in the image."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2396151", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344352.jpg", "positive_caption": ["There are exactly 11 words on the sign."], "negative_caption": ["There are exactly 2 words on the sign."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344352", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344799.jpg", "positive_caption": ["There are exactly 11 bananas being held."], "negative_caption": ["There are exactly 2 bananas being held."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344799", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367131.jpg", "positive_caption": ["There are exactly 12 donuts in a box."], "negative_caption": ["There are exactly 3 donuts in a box."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2367131", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369372.jpg", "positive_caption": ["There are exactly 12 kids."], "negative_caption": ["There is exactly 1 kid."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2369372", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380536.jpg", "positive_caption": ["There are exactly 12 signs in the image."], "negative_caption": ["There are exactly 2 signs in the image."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2380536", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401031.jpg", "positive_caption": ["There are exactly 12 cows."], "negative_caption": ["There are exactly 2 cows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2401031", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402691.jpg", "positive_caption": ["There are exactly 12 numbers on the clock."], "negative_caption": ["There are exactly 0 numbers on the clock."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2402691", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403164.jpg", "positive_caption": ["There are exactly 12 roman numerals on the clock."], "negative_caption": ["There are exactly 3 roman numerals on the clock."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2403164", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385592.jpg", "positive_caption": ["There are exactly 12 people in the photo on motorbikes."], "negative_caption": ["There are exactly 2 people in the photo on motorbikes."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2385592", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417056.jpg", "positive_caption": ["There are exactly 12 numbers."], "negative_caption": ["There are exactly 0 numbers."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2417056", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327185.jpg", "positive_caption": ["There are exactly 12 green peppers visible in the box to the left."], "negative_caption": ["There are exactly 0 green peppers visible in the box to the left."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2327185", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332631.jpg", "positive_caption": ["There are exactly 12 numbers on the clock."], "negative_caption": ["There is exactly 1 number on the clock."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2332631", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346784.jpg", "positive_caption": ["There are exactly 12 numbers on the clock."], "negative_caption": ["There are exactly 2 numbers on the clock."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2346784", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348158.jpg", "positive_caption": ["There are exactly 12 sheep in the picture."], "negative_caption": ["There are exactly 0 sheep in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2348158", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352424.jpg", "positive_caption": ["There are exactly 12 windows visible."], "negative_caption": ["There are exactly 0 windows visible."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2352424", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368500.jpg", "positive_caption": ["There are exactly 10 people in the image."], "negative_caption": ["There are exactly 2 people in the image."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2368500", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374900.jpg", "positive_caption": ["Exactly 10 flags can be seen."], "negative_caption": ["Exactly 3 flags can be seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2374900", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383243.jpg", "positive_caption": ["There are exactly 10 people wearing coats."], "negative_caption": ["There is exactly 1 person wearing coats."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2383243", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398494.jpg", "positive_caption": ["There are exactly 10 knives in the picture."], "negative_caption": ["There are exactly 2 knives in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2398494", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406219.jpg", "positive_caption": ["There are exactly 10 tall trees."], "negative_caption": ["There is exactly 1 tall tree."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2406219", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414484.jpg", "positive_caption": ["There are exactly 10 animals."], "negative_caption": ["There are exactly 2 animals."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2414484", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713121.jpg", "positive_caption": ["There are exactly 10 wine bottle on the table and counter."], "negative_caption": ["There is exactly 1 wine bottle on the table and counter."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_713121", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316017.jpg", "positive_caption": ["There are exactly 10 people on the train."], "negative_caption": ["There are exactly 3 people on the train."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2316017", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331299.jpg", "positive_caption": ["There are exactly 10 people on the street."], "negative_caption": ["There is exactly 1 person on the street."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2331299", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333955.jpg", "positive_caption": ["There are exactly 10 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2333955", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338184.jpg", "positive_caption": ["There are exactly 10 pieces of fruit."], "negative_caption": ["There are exactly 0 pieces of fruit."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2338184", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1160241.jpg", "positive_caption": ["There are exactly 10 cars parked behind the boats."], "negative_caption": ["There are exactly 2 cars parked behind the boats."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1160241", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342166.jpg", "positive_caption": ["There are exactly 10 windows."], "negative_caption": ["There are exactly 3 windows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342166", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342245.jpg", "positive_caption": ["There are exactly 10 lamps."], "negative_caption": ["There is exactly 1 lamp."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2342245", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345435.jpg", "positive_caption": ["There are exactly 10 poles."], "negative_caption": ["There are exactly 0 poles."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2345435", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349642.jpg", "positive_caption": ["There are exactly 10 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2349642", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354114.jpg", "positive_caption": ["There are exactly 10 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2354114", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366414.jpg", "positive_caption": ["There are exactly 13 pieces of art."], "negative_caption": ["There is exactly 1 piece of art."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2366414", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591945.jpg", "positive_caption": ["There are exactly 13 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1591945", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395142.jpg", "positive_caption": ["There are exactly 13 people standing on the platform to the right."], "negative_caption": ["There is exactly 1 person standing on the platform to the right."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2395142", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411646.jpg", "positive_caption": ["There are exactly 13 bunches."], "negative_caption": ["There are exactly 0 bunches."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2411646", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336075.jpg", "positive_caption": ["There are exactly 13 glasses on the top table."], "negative_caption": ["There are exactly 2 glasses on the top table."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2336075", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338537.jpg", "positive_caption": ["Exactly 13 vases can be seen."], "negative_caption": ["Exactly 0 vases can be seen."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2338537", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377974.jpg", "positive_caption": ["There are exactly 35 lights on the front of this bus."], "negative_caption": ["There are exactly 3 lights on the front of this bus."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2377974", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591825.jpg", "positive_caption": ["There are exactly 15 kids in the pictures."], "negative_caption": ["There is exactly 1 kid in the pictures."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1591825", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392781.jpg", "positive_caption": ["There are exactly 15 clocks drawn."], "negative_caption": ["There are exactly 2 clocks drawn."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2392781", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399914.jpg", "positive_caption": ["There are exactly 15 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2399914", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318628.jpg", "positive_caption": ["There are exactly 15 bears."], "negative_caption": ["There is exactly 1 bear."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2318628", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344175.jpg", "positive_caption": ["There are exactly 15 signs on the pole."], "negative_caption": ["There are exactly 0 signs on the pole."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2344175", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387072.jpg", "positive_caption": ["There are exactly 20 zebras pictured here."], "negative_caption": ["There are exactly 3 zebras pictured here."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2387072", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392762.jpg", "positive_caption": ["There are exactly 20 pepperonis."], "negative_caption": ["There are exactly 3 pepperonis."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2392762", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330987.jpg", "positive_caption": ["There are exactly 20 scooters shown."], "negative_caption": ["There are exactly 0 scooters shown."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2330987", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355520.jpg", "positive_caption": ["There are exactly 20 buttons on the phone."], "negative_caption": ["There are exactly 0 buttons on the phone."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2355520", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391324.jpg", "positive_caption": ["There are exactly 16 umbrellas."], "negative_caption": ["There are exactly 3 umbrellas."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2391324", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397902.jpg", "positive_caption": ["There are exactly 18 sections make up the doors and border of doors."], "negative_caption": ["There are exactly 0 sections make up the doors and border of doors."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2397902", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335679.jpg", "positive_caption": ["There are exactly 22 windows."], "negative_caption": ["There are exactly 2 windows."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_2335679", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1160223.jpg", "positive_caption": ["There are exactly 30 miles per hour permitted on the street during normal day hours."], "negative_caption": ["There is exactly 1 mile per hour permitted on the street during normal day hours."], "original_file_name": "counting-adversarial", "dataset": "visual7w", "key": "counting_visual7w_1160223", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396743.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2396743", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383458.jpg", "positive_caption": ["There are exactly 0 people in the image."], "negative_caption": ["There are exactly 4 people in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2383458", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375454.jpg", "positive_caption": ["There are exactly 4 dishes in the picture."], "negative_caption": ["There are exactly 12 dishes in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375454", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359678.jpg", "positive_caption": ["There are exactly 3 birds."], "negative_caption": ["There are exactly 12 birds."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359678", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390850.jpg", "positive_caption": ["There are exactly 0 people in the water."], "negative_caption": ["There is exactly 1 person in the water."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2390850", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370690.jpg", "positive_caption": ["There are exactly 0 people pictured here."], "negative_caption": ["There are exactly 2 people pictured here."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370690", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358654.jpg", "positive_caption": ["You see exactly 5 toes."], "negative_caption": ["You see exactly 1 toe."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2358654", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401699.jpg", "positive_caption": ["There are exactly 0 windows in the building."], "negative_caption": ["There are exactly 12 windows in the building."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401699", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382056.jpg", "positive_caption": ["There are exactly 5 buses."], "negative_caption": ["There are exactly 0 buses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2382056", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365548.jpg", "positive_caption": ["There are exactly 4 people pictured."], "negative_caption": ["There are exactly 6 people pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365548", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362033.jpg", "positive_caption": ["There is exactly 1 motorcycle."], "negative_caption": ["There are exactly 5 motorcycles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362033", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346078.jpg", "positive_caption": ["There are exactly 6 horses."], "negative_caption": ["There are exactly 2 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2346078", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364670.jpg", "positive_caption": ["There are exactly 2 lamp post."], "negative_caption": ["There is exactly 1 lamp post."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364670", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387506.jpg", "positive_caption": ["There are exactly 6 treats pictured."], "negative_caption": ["There are exactly 2 treats pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2387506", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348158.jpg", "positive_caption": ["There are exactly 12 sheep in the picture."], "negative_caption": ["There are exactly 8 sheep in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2348158", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372975.jpg", "positive_caption": ["There is exactly 1 player."], "negative_caption": ["There are exactly 4 players."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372975", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361023.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 4 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361023", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417056.jpg", "positive_caption": ["There are exactly 12 numbers."], "negative_caption": ["There are exactly 8 numbers."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2417056", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392692.jpg", "positive_caption": ["There are exactly 14 people featured."], "negative_caption": ["There are exactly 2 people featured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2392692", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413600.jpg", "positive_caption": ["There are exactly 0 chickens."], "negative_caption": ["There are exactly 4 chickens."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2413600", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375378.jpg", "positive_caption": ["There are exactly 2 tires."], "negative_caption": ["There are exactly 5 tires."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375378", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367452.jpg", "positive_caption": ["There are exactly 2 boys."], "negative_caption": ["There are exactly 4 boys."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367452", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403286.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There are exactly 12 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403286", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592935.jpg", "positive_caption": ["There are exactly 3 bananas in the bowl."], "negative_caption": ["There are exactly 5 bananas in the bowl."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592935", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365707.jpg", "positive_caption": ["There is exactly 1 kite."], "negative_caption": ["There are exactly 3 kites."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365707", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385400.jpg", "positive_caption": ["There are exactly 7 ties."], "negative_caption": ["There are exactly 8 ties."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2385400", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393085.jpg", "positive_caption": ["There are exactly 0 people with the bears."], "negative_caption": ["There is exactly 1 person with the bears."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2393085", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407693.jpg", "positive_caption": ["There are exactly 8 giraffes."], "negative_caption": ["There are exactly 6 giraffes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2407693", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370248.jpg", "positive_caption": ["There are exactly 3 towels."], "negative_caption": ["There are exactly 6 towels."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370248", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367505.jpg", "positive_caption": ["There are exactly 3 toilet paper rolls."], "negative_caption": ["There are exactly 13 toilet paper rolls."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367505", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372350.jpg", "positive_caption": ["There is exactly 1 banana."], "negative_caption": ["There are exactly 2 bananas."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372350", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591945.jpg", "positive_caption": ["There are exactly 13 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591945", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368143.jpg", "positive_caption": ["3 bottles have blue caps."], "negative_caption": ["4 bottles have blue caps."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368143", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375646.jpg", "positive_caption": ["There are exactly 3 people under the scissors."], "negative_caption": ["There is exactly 1 person under the scissors."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375646", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363617.jpg", "positive_caption": ["There is exactly 1 pitcher visible."], "negative_caption": ["There are exactly 0 pitchers visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363617", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380605.jpg", "positive_caption": ["There are exactly 4 birds pictured."], "negative_caption": ["There are exactly 8 birds pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2380605", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372073.jpg", "positive_caption": ["There are exactly 4 people in the picture."], "negative_caption": ["There are exactly 5 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372073", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374341.jpg", "positive_caption": ["There is exactly 1 person in the photo."], "negative_caption": ["There are exactly 4 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374341", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355921.jpg", "positive_caption": ["There are exactly 7 traffic lights red."], "negative_caption": ["There are exactly 2 traffic lights red."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2355921", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150392.jpg", "positive_caption": ["There are exactly 0 clouds in sight."], "negative_caption": ["There are exactly 3 clouds in sight."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150392", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368105.jpg", "positive_caption": ["There are exactly 3 boats on the side of the building."], "negative_caption": ["There are exactly 11 boats on the side of the building."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368105", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378479.jpg", "positive_caption": ["There are exactly 3 hands."], "negative_caption": ["There are exactly 4 hands."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2378479", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401031.jpg", "positive_caption": ["There are exactly 12 cows."], "negative_caption": ["There are exactly 6 cows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401031", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360773.jpg", "positive_caption": ["There are exactly 2 giraffes shown."], "negative_caption": ["There are exactly 4 giraffes shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360773", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379339.jpg", "positive_caption": ["There are exactly 5 stories to the building."], "negative_caption": ["There is exactly 1 storie to the building."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2379339", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367399.jpg", "positive_caption": ["There are exactly 8 horses."], "negative_caption": ["There are exactly 2 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367399", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365480.jpg", "positive_caption": ["There is exactly 1 chair."], "negative_caption": ["There are exactly 4 chairs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365480", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399146.jpg", "positive_caption": ["There are exactly 5 colors on the Red Man sign."], "negative_caption": ["There are exactly 3 colors on the Red Man sign."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2399146", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378665.jpg", "positive_caption": ["There are exactly 3 white sheep babies."], "negative_caption": ["There are exactly 5 white sheep babies."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2378665", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362055.jpg", "positive_caption": ["There are exactly 7 men."], "negative_caption": ["There are exactly 8 men."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362055", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361568.jpg", "positive_caption": ["There are exactly 2 men playing frisbee."], "negative_caption": ["There are exactly 3 men playing frisbee."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361568", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332631.jpg", "positive_caption": ["There are exactly 12 numbers on the clock."], "negative_caption": ["There are exactly 0 numbers on the clock."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2332631", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393653.jpg", "positive_caption": ["There are exactly 4 colors in the girl's shirt."], "negative_caption": ["There are exactly 5 colors in the girl's shirt."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2393653", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372537.jpg", "positive_caption": ["There are exactly 3 black boats."], "negative_caption": ["There are exactly 0 black boats."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372537", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369629.jpg", "positive_caption": ["There are exactly 6 items on the black bar."], "negative_caption": ["There are exactly 0 items on the black bar."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369629", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364723.jpg", "positive_caption": ["2 men have glasses."], "negative_caption": ["4 men have glasses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364723", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353303.jpg", "positive_caption": ["There are exactly 8 cars."], "negative_caption": ["There are exactly 5 cars."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2353303", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388164.jpg", "positive_caption": ["There are exactly 0 animals in the shot."], "negative_caption": ["There are exactly 4 animals in the shot."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2388164", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394458.jpg", "positive_caption": ["There are exactly 5 people in the scene."], "negative_caption": ["There are exactly 0 people in the scene."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2394458", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415024.jpg", "positive_caption": ["There are exactly 4 windows around the vines."], "negative_caption": ["There are exactly 2 windows around the vines."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2415024", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363291.jpg", "positive_caption": ["3 tires can we see on the plane."], "negative_caption": ["1 tire can we see on the plane."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363291", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381297.jpg", "positive_caption": ["There are exactly 3 trains."], "negative_caption": ["There are exactly 5 trains."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381297", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374498.jpg", "positive_caption": ["There is exactly 1 toilet seat."], "negative_caption": ["There are exactly 4 toilet seats."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374498", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404069.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2404069", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395349.jpg", "positive_caption": ["There are exactly 6 chairs around the larger table."], "negative_caption": ["There are exactly 4 chairs around the larger table."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2395349", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374130.jpg", "positive_caption": ["There is exactly 1 child looking at the tree."], "negative_caption": ["There are exactly 2 children looking at the tree."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374130", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388041.jpg", "positive_caption": ["There are exactly 9 dots between the numbers."], "negative_caption": ["There is exactly 1 dot between the numbers."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2388041", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381964.jpg", "positive_caption": ["There are exactly 3 musicains in the photo."], "negative_caption": ["There are exactly 13 musicains in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381964", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403538.jpg", "positive_caption": ["There are exactly 4 slices of pizza."], "negative_caption": ["There are exactly 2 slices of pizza."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403538", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381861.jpg", "positive_caption": ["There are exactly 6 people."], "negative_caption": ["There are exactly 5 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381861", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337790.jpg", "positive_caption": ["There are exactly 6 lights."], "negative_caption": ["There are exactly 7 lights."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2337790", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371625.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371625", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285965.jpg", "positive_caption": ["There is exactly 1 window."], "negative_caption": ["There are exactly 0 windows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_285965", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406002.jpg", "positive_caption": ["There are exactly 8 tomatoes on the plate."], "negative_caption": ["There are exactly 0 tomatoes on the plate."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2406002", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356436.jpg", "positive_caption": ["There are exactly 9 pictures on the walls."], "negative_caption": ["There are exactly 0 pictures on the walls."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2356436", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377835.jpg", "positive_caption": ["3 people can be seen."], "negative_caption": ["6 people can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377835", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363773.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363773", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367721.jpg", "positive_caption": ["There are exactly 2 people in the picture."], "negative_caption": ["There are exactly 6 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367721", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336300.jpg", "positive_caption": ["There are exactly 5 zebras."], "negative_caption": ["There are exactly 6 zebras."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2336300", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348424.jpg", "positive_caption": ["You see exactly 5 headrests."], "negative_caption": ["You see exactly 6 headrests."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2348424", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371080.jpg", "positive_caption": ["There is exactly 1 microwave."], "negative_caption": ["There are exactly 2 microwaves."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371080", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371752.jpg", "positive_caption": ["There are exactly 3 people on the field."], "negative_caption": ["There are exactly 6 people on the field."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371752", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150325.jpg", "positive_caption": ["There are exactly 3 balloons."], "negative_caption": ["There are exactly 5 balloons."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150325", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372081.jpg", "positive_caption": ["There are exactly 5 jars pictured."], "negative_caption": ["There are exactly 7 jars pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372081", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393661.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2393661", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371980.jpg", "positive_caption": ["There is exactly 1 kind of animals in the picture."], "negative_caption": ["There are exactly 0 kinds of animals in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371980", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373955.jpg", "positive_caption": ["There are exactly 2 dogs."], "negative_caption": ["There is exactly 1 dog."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373955", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374843.jpg", "positive_caption": ["There are exactly 6 umbrellas."], "negative_caption": ["There are exactly 8 umbrellas."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374843", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381535.jpg", "positive_caption": ["There are exactly 3 planes shown."], "negative_caption": ["There are exactly 4 planes shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381535", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382325.jpg", "positive_caption": ["There are exactly 3 pickles."], "negative_caption": ["There are exactly 13 pickles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2382325", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365245.jpg", "positive_caption": ["There are exactly 6 cows in the picture."], "negative_caption": ["There are exactly 5 cows in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365245", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404018.jpg", "positive_caption": ["There are exactly 5 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2404018", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402691.jpg", "positive_caption": ["There are exactly 12 numbers on the clock."], "negative_caption": ["There are exactly 3 numbers on the clock."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2402691", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377401.jpg", "positive_caption": ["There are exactly 3 giraffes."], "negative_caption": ["There are exactly 2 giraffes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377401", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592658.jpg", "positive_caption": ["There are exactly 9 mirrors on the lawn."], "negative_caption": ["There are exactly 0 mirrors on the lawn."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592658", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377654.jpg", "positive_caption": ["There are exactly 3 zebras."], "negative_caption": ["There are exactly 8 zebras."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377654", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391547.jpg", "positive_caption": ["There are exactly 6 pieces of luggage in the image."], "negative_caption": ["There are exactly 2 pieces of luggage in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2391547", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374162.jpg", "positive_caption": ["There are exactly 3 books on the table."], "negative_caption": ["There are exactly 0 books on the table."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374162", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367575.jpg", "positive_caption": ["There is exactly 1 man in the picture."], "negative_caption": ["There are exactly 3 men in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367575", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150527.jpg", "positive_caption": ["There are exactly 15 cows."], "negative_caption": ["There are exactly 7 cows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150527", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340658.jpg", "positive_caption": ["There are exactly 7 kites flying."], "negative_caption": ["There are exactly 0 kites flying."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2340658", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377550.jpg", "positive_caption": ["There are exactly 5 people standing."], "negative_caption": ["There are exactly 3 people standing."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377550", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349621.jpg", "positive_caption": ["There are exactly 5 flowers."], "negative_caption": ["There are exactly 10 flowers."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2349621", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412019.jpg", "positive_caption": ["There are exactly 5 sun pictures across the skirt of the settee."], "negative_caption": ["There are exactly 7 sun pictures across the skirt of the settee."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2412019", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406033.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 6 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2406033", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363712.jpg", "positive_caption": ["You see exactly 4 horses in the image."], "negative_caption": ["You see exactly 3 horses in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363712", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366431.jpg", "positive_caption": ["There is exactly 1 tv."], "negative_caption": ["There are exactly 5 tvs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366431", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362744.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 2 giraffe."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362744", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367490.jpg", "positive_caption": ["There are exactly 4 motorcycles."], "negative_caption": ["There are exactly 3 motorcycles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367490", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400175.jpg", "positive_caption": ["There are exactly 6 spectators in the photo."], "negative_caption": ["There are exactly 8 spectators in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400175", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367942.jpg", "positive_caption": ["There are exactly 4 propellers on the plane."], "negative_caption": ["There are exactly 8 propellers on the plane."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367942", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371495.jpg", "positive_caption": ["There is exactly 1 person in this picture."], "negative_caption": ["There are exactly 3 people in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371495", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591862.jpg", "positive_caption": ["There are exactly 8 empty bowls visible."], "negative_caption": ["There are exactly 2 empty bowls visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591862", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373511.jpg", "positive_caption": ["There is exactly 1 person in this picture."], "negative_caption": ["There are exactly 3 people in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373511", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316291.jpg", "positive_caption": ["There are exactly 8 people."], "negative_caption": ["There are exactly 4 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2316291", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322213.jpg", "positive_caption": ["There are exactly 14 pumpkins."], "negative_caption": ["There are exactly 11 pumpkins."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2322213", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150407.jpg", "positive_caption": ["There are exactly 6 onion rings."], "negative_caption": ["There are exactly 2 onion rings."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150407", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380468.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2380468", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318640.jpg", "positive_caption": ["There are exactly 6 green leaves on the pizza."], "negative_caption": ["There are exactly 8 green leaves on the pizza."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2318640", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385676.jpg", "positive_caption": ["There are exactly 9 pieces of fruit."], "negative_caption": ["There are exactly 10 pieces of fruit."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2385676", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375481.jpg", "positive_caption": ["There are exactly 3 ducks."], "negative_caption": ["There are exactly 5 ducks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375481", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395142.jpg", "positive_caption": ["There are exactly 13 people standing on the platform to the right."], "negative_caption": ["There are exactly 5 people standing on the platform to the right."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2395142", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375379.jpg", "positive_caption": ["There are exactly 2 birds."], "negative_caption": ["There are exactly 5 birds."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375379", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362248.jpg", "positive_caption": ["There is exactly 1 person wearing a yellow dress."], "negative_caption": ["There are exactly 2 people wearing a yellow dress."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362248", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389326.jpg", "positive_caption": ["There are exactly 0 animals."], "negative_caption": ["There are exactly 4 animals."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2389326", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416821.jpg", "positive_caption": ["There are exactly 4 flowers in the vase."], "negative_caption": ["There are exactly 13 flowers in the vase."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2416821", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371725.jpg", "positive_caption": ["There are exactly 2 street signs."], "negative_caption": ["There is exactly 1 street sign."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371725", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375522.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375522", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372021.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 5 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372021", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368830.jpg", "positive_caption": ["There is exactly 1 clock."], "negative_caption": ["There are exactly 2 clocks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368830", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416634.jpg", "positive_caption": ["There are exactly 0 dolphins visible."], "negative_caption": ["There are exactly 2 dolphins visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2416634", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381158.jpg", "positive_caption": ["There are exactly 3 horses in the picture."], "negative_caption": ["There are exactly 6 horses in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381158", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379573.jpg", "positive_caption": ["There are exactly 4 train tracks."], "negative_caption": ["There are exactly 5 train tracks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2379573", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389519.jpg", "positive_caption": ["There are exactly 4 bikes on the rack."], "negative_caption": ["There are exactly 2 bikes on the rack."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2389519", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377745.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377745", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380044.jpg", "positive_caption": ["There are exactly 3 vehicles shown."], "negative_caption": ["There are exactly 5 vehicles shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2380044", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316731.jpg", "positive_caption": ["There are exactly 5 bears in the photo."], "negative_caption": ["There are exactly 3 bears in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2316731", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395077.jpg", "positive_caption": ["There are exactly 0 animals in the photo."], "negative_caption": ["There are exactly 2 animals in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2395077", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360156.jpg", "positive_caption": ["There are exactly 0 people shown."], "negative_caption": ["There are exactly 3 people shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360156", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344908.jpg", "positive_caption": ["There are exactly 5 sheep."], "negative_caption": ["There are exactly 3 sheep."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2344908", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365504.jpg", "positive_caption": ["There is exactly 1 giraffe in the picture."], "negative_caption": ["There are exactly 3 giraffes in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365504", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399167.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2399167", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374116.jpg", "positive_caption": ["There is exactly 1 woman visible."], "negative_caption": ["There are exactly 5 women visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374116", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331656.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2331656", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371584.jpg", "positive_caption": ["There are exactly 2 wheels on the gate."], "negative_caption": ["There is exactly 1 wheel on the gate."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371584", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363965.jpg", "positive_caption": ["4 ford logos can be seen."], "negative_caption": ["1 ford logo can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363965", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330359.jpg", "positive_caption": ["There are exactly 6 benches on this road."], "negative_caption": ["There are exactly 5 benches on this road."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2330359", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591832.jpg", "positive_caption": ["There are exactly 9 lights."], "negative_caption": ["There are exactly 4 lights."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591832", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400778.jpg", "positive_caption": ["6 giraffes can be seen."], "negative_caption": ["8 giraffes can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400778", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317793.jpg", "positive_caption": ["There are exactly 7 food items on the grill."], "negative_caption": ["There are exactly 5 food items on the grill."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2317793", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372475.jpg", "positive_caption": ["There is exactly 1 animal."], "negative_caption": ["There are exactly 4 animals."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372475", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365369.jpg", "positive_caption": ["There are exactly 3 umbrellas shown."], "negative_caption": ["There are exactly 4 umbrellas shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365369", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390830.jpg", "positive_caption": ["There are exactly 6 whole pastries shown."], "negative_caption": ["There are exactly 5 whole pastries shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2390830", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375716.jpg", "positive_caption": ["There are exactly 3 giraffe shown."], "negative_caption": ["There are exactly 0 giraffe shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375716", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361089.jpg", "positive_caption": ["There are exactly 2 street lights visible."], "negative_caption": ["There are exactly 0 street lights visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361089", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401147.jpg", "positive_caption": ["There are exactly 8 sheep."], "negative_caption": ["There are exactly 5 sheep."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401147", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339637.jpg", "positive_caption": ["There are exactly 2 cows shown."], "negative_caption": ["There are exactly 5 cows shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2339637", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367780.jpg", "positive_caption": ["There is exactly 1 pizza."], "negative_caption": ["There are exactly 5 pizzas."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367780", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335163.jpg", "positive_caption": ["6 people have umbrellas."], "negative_caption": ["5 people have umbrellas."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2335163", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1.jpg", "positive_caption": ["There are exactly 4 cars parked."], "negative_caption": ["There are exactly 5 cars parked."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393805.jpg", "positive_caption": ["There are exactly 0 animals."], "negative_caption": ["There are exactly 2 animals."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2393805", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591933.jpg", "positive_caption": ["There are exactly 3 do not enter signs."], "negative_caption": ["There are exactly 2 do not enter signs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591933", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362000.jpg", "positive_caption": ["There is exactly 1 person in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362000", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364719.jpg", "positive_caption": ["There are exactly 2 dogs pictured."], "negative_caption": ["There is exactly 1 dog pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364719", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360779.jpg", "positive_caption": ["There are exactly 0 people in this photo."], "negative_caption": ["There are exactly 5 people in this photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360779", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159614.jpg", "positive_caption": ["There are exactly 3 many chairs at the table."], "negative_caption": ["There is exactly 1 many chair at the table."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1159614", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713051.jpg", "positive_caption": ["There are exactly 6 tires on one side of the truck."], "negative_caption": ["There are exactly 2 tires on one side of the truck."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_713051", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366469.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 5 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366469", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392883.jpg", "positive_caption": ["There are exactly 7 traffic lights seen."], "negative_caption": ["There are exactly 10 traffic lights seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2392883", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376064.jpg", "positive_caption": ["There are exactly 2 bears."], "negative_caption": ["There are exactly 3 bears."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2376064", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365048.jpg", "positive_caption": ["There are exactly 8 people in this room."], "negative_caption": ["There are exactly 4 people in this room."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365048", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360527.jpg", "positive_caption": ["There are exactly 2 elephants."], "negative_caption": ["There is exactly 1 elephant."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360527", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364948.jpg", "positive_caption": ["There is exactly 1 elephant in the picture."], "negative_caption": ["There are exactly 4 elephants in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364948", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369085.jpg", "positive_caption": ["There is exactly 1 man."], "negative_caption": ["There are exactly 3 men."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369085", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285933.jpg", "positive_caption": ["There are exactly 4 blueberries."], "negative_caption": ["There are exactly 2 blueberries."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_285933", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409635.jpg", "positive_caption": ["There are exactly 4 people on the sidewalk."], "negative_caption": ["There are exactly 6 people on the sidewalk."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2409635", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336401.jpg", "positive_caption": ["There are exactly 5 onion slices in the photo."], "negative_caption": ["There are exactly 7 onion slices in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2336401", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348273.jpg", "positive_caption": ["There are exactly 9 items in there."], "negative_caption": ["There are exactly 2 items in there."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2348273", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401721.jpg", "positive_caption": ["There are exactly 8 slices."], "negative_caption": ["There are exactly 7 slices."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401721", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713121.jpg", "positive_caption": ["There are exactly 10 wine bottle on the table and counter."], "negative_caption": ["There are exactly 3 wine bottle on the table and counter."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_713121", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334657.jpg", "positive_caption": ["There are exactly 5 train cars."], "negative_caption": ["There are exactly 3 train cars."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2334657", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359796.jpg", "positive_caption": ["There are exactly 3 elephants in the picture."], "negative_caption": ["There are exactly 0 elephants in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359796", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362071.jpg", "positive_caption": ["There is exactly 1 car pictured."], "negative_caption": ["There are exactly 2 cars pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362071", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373151.jpg", "positive_caption": ["There are exactly 3 of the animals giraffes."], "negative_caption": ["There are exactly 14 of the animals giraffes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373151", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380536.jpg", "positive_caption": ["There are exactly 12 signs in the image."], "negative_caption": ["There are exactly 10 signs in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2380536", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367016.jpg", "positive_caption": ["There is exactly 1 pencil shown."], "negative_caption": ["There are exactly 3 pencils shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367016", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324760.jpg", "positive_caption": ["There are exactly 8 horses."], "negative_caption": ["There are exactly 5 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2324760", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361093.jpg", "positive_caption": ["There is exactly 1 person snowboarding."], "negative_caption": ["There are exactly 4 people snowboarding."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361093", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366695.jpg", "positive_caption": ["There is exactly 1 train."], "negative_caption": ["There are exactly 3 trains."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366695", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403793.jpg", "positive_caption": ["There are exactly 4 wheels on the skateboard."], "negative_caption": ["There are exactly 6 wheels on the skateboard."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403793", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408513.jpg", "positive_caption": ["There are exactly 6 horses."], "negative_caption": ["There are exactly 2 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2408513", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365510.jpg", "positive_caption": ["There are exactly 2 dogs in the water."], "negative_caption": ["There are exactly 4 dogs in the water."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365510", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366739.jpg", "positive_caption": ["There is exactly 1 person in the picture."], "negative_caption": ["There are exactly 4 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366739", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402074.jpg", "positive_caption": ["There are exactly 4 red vehicles."], "negative_caption": ["There are exactly 0 red vehicles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2402074", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_18.jpg", "positive_caption": ["There is exactly 1 soda bottle on the table."], "negative_caption": ["There are exactly 0 soda bottles on the table."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_18", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416865.jpg", "positive_caption": ["There are exactly 5 black sheep shown."], "negative_caption": ["There is exactly 1 black sheep shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2416865", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382949.jpg", "positive_caption": ["There is exactly 1 wine bottle on the rack."], "negative_caption": ["There are exactly 7 wine bottles on the rack."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2382949", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373170.jpg", "positive_caption": ["There are exactly 2 animals visible in the picture."], "negative_caption": ["There is exactly 1 animal visible in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373170", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334682.jpg", "positive_caption": ["There are exactly 7 cars in the photo."], "negative_caption": ["There are exactly 5 cars in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2334682", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366137.jpg", "positive_caption": ["There are exactly 12 legs in the picture."], "negative_caption": ["There are exactly 2 legs in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366137", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344175.jpg", "positive_caption": ["There are exactly 15 signs on the pole."], "negative_caption": ["There are exactly 16 signs on the pole."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2344175", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400052.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400052", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363853.jpg", "positive_caption": ["There are exactly 2 bicycles."], "negative_caption": ["There are exactly 4 bicycles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363853", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378613.jpg", "positive_caption": ["There are exactly 9 parachutes in the sky."], "negative_caption": ["There are exactly 8 parachutes in the sky."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2378613", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411632.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2411632", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360522.jpg", "positive_caption": ["There are exactly 3 bottles on the counter."], "negative_caption": ["There is exactly 1 bottle on the counter."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360522", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410496.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 7 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2410496", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359614.jpg", "positive_caption": ["There are exactly 2 zebras."], "negative_caption": ["There are exactly 5 zebras."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359614", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373121.jpg", "positive_caption": ["There are exactly 0 clouds in the sky."], "negative_caption": ["There are exactly 2 clouds in the sky."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373121", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592844.jpg", "positive_caption": ["There are exactly 0 towels."], "negative_caption": ["There are exactly 2 towels."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592844", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393147.jpg", "positive_caption": ["There are exactly 7 people in the photo."], "negative_caption": ["There are exactly 8 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2393147", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592881.jpg", "positive_caption": ["There are exactly 6 blue arrows on the sign."], "negative_caption": ["There are exactly 9 blue arrows on the sign."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592881", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362500.jpg", "positive_caption": ["There are exactly 5 black cattle."], "negative_caption": ["There are exactly 6 black cattle."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362500", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397330.jpg", "positive_caption": ["There are exactly 6 pieces of pizza."], "negative_caption": ["There are exactly 9 pieces of pizza."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2397330", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389022.jpg", "positive_caption": ["There are exactly 4 legs on the seat."], "negative_caption": ["There are exactly 3 legs on the seat."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2389022", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361946.jpg", "positive_caption": ["There is exactly 1 couch."], "negative_caption": ["There are exactly 4 couches."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361946", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408874.jpg", "positive_caption": ["There are exactly 7 spindles on the chair."], "negative_caption": ["There is exactly 1 spindle on the chair."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2408874", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322101.jpg", "positive_caption": ["There are exactly 6 giraffes in the picture."], "negative_caption": ["There are exactly 7 giraffes in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2322101", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348566.jpg", "positive_caption": ["There are exactly 6 people."], "negative_caption": ["There are exactly 5 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2348566", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369718.jpg", "positive_caption": ["There is exactly 1 dog."], "negative_caption": ["There are exactly 2 dogs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369718", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396309.jpg", "positive_caption": ["There are exactly 0 planes shown."], "negative_caption": ["There is exactly 1 plane shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2396309", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347382.jpg", "positive_caption": ["There are exactly 8 things outside of the purse."], "negative_caption": ["There are exactly 0 things outside of the purse."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2347382", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591804.jpg", "positive_caption": ["There are exactly 6 wheels on this display."], "negative_caption": ["There are exactly 3 wheels on this display."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591804", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381009.jpg", "positive_caption": ["There are exactly 8 Numbers on the sign."], "negative_caption": ["There are exactly 6 Numbers on the sign."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381009", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409479.jpg", "positive_caption": ["5 vases can be seen."], "negative_caption": ["4 vases can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2409479", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366329.jpg", "positive_caption": ["There are exactly 2 people in the photo."], "negative_caption": ["There are exactly 6 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366329", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374904.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 4 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374904", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382639.jpg", "positive_caption": ["There are exactly 7 pots on the top shelf."], "negative_caption": ["There are exactly 8 pots on the top shelf."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2382639", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362651.jpg", "positive_caption": ["There are exactly 2 windows in the room."], "negative_caption": ["There is exactly 1 window in the room."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362651", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330558.jpg", "positive_caption": ["There are exactly 6 chairs in the photo."], "negative_caption": ["There are exactly 2 chairs in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2330558", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364894.jpg", "positive_caption": ["There are exactly 2 bears in the photo."], "negative_caption": ["There are exactly 0 bears in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364894", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370341.jpg", "positive_caption": ["There is exactly 1 teddy bear."], "negative_caption": ["There are exactly 2 teddy bears."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370341", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377383.jpg", "positive_caption": ["There are exactly 5 ducks."], "negative_caption": ["There are exactly 2 ducks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377383", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379900.jpg", "positive_caption": ["There are exactly 4 doors."], "negative_caption": ["There are exactly 7 doors."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2379900", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344897.jpg", "positive_caption": ["There are exactly 5 people pictured sitting in the stands."], "negative_caption": ["There are exactly 3 people pictured sitting in the stands."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2344897", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362471.jpg", "positive_caption": ["The elephants have exactly 2 tusks."], "negative_caption": ["The elephants have exactly 6 tusks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362471", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372214.jpg", "positive_caption": ["There are exactly 3 cows."], "negative_caption": ["There are exactly 8 cows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372214", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393355.jpg", "positive_caption": ["There are exactly 4 players or shown."], "negative_caption": ["There are exactly 5 players or shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2393355", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382902.jpg", "positive_caption": ["There are exactly 5 light posts."], "negative_caption": ["There are exactly 7 light posts."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2382902", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367907.jpg", "positive_caption": ["There is exactly 1 hand."], "negative_caption": ["There are exactly 3 hands."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367907", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367703.jpg", "positive_caption": ["There is exactly 1 motorcycle."], "negative_caption": ["There are exactly 4 motorcycles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367703", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363189.jpg", "positive_caption": ["There is exactly 1 bench."], "negative_caption": ["There are exactly 0 benches."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363189", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363534.jpg", "positive_caption": ["There are exactly 2 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363534", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409712.jpg", "positive_caption": ["There are exactly 8 kites visible in the sky."], "negative_caption": ["There are exactly 0 kites visible in the sky."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2409712", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374318.jpg", "positive_caption": ["There are exactly 2 eggs."], "negative_caption": ["There are exactly 0 eggs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374318", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368514.jpg", "positive_caption": ["There are exactly 7 chairs."], "negative_caption": ["There are exactly 4 chairs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368514", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360349.jpg", "positive_caption": ["There are exactly 2 giraffes in the picture."], "negative_caption": ["There are exactly 3 giraffes in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360349", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372964.jpg", "positive_caption": ["There is exactly 1 person in this photo."], "negative_caption": ["There are exactly 7 people in this photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372964", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328442.jpg", "positive_caption": ["There are exactly 5 teddy bears in the picture."], "negative_caption": ["There is exactly 1 teddy bear in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2328442", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374489.jpg", "positive_caption": ["There is exactly 1 zebra."], "negative_caption": ["There are exactly 4 zebras."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374489", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360434.jpg", "positive_caption": ["There are exactly 4 signs pictured."], "negative_caption": ["There are exactly 3 signs pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360434", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405038.jpg", "positive_caption": ["There are exactly 6 goats."], "negative_caption": ["There are exactly 2 goats."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2405038", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150430.jpg", "positive_caption": ["There are exactly 5 wear goggles."], "negative_caption": ["There are exactly 3 wear goggles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150430", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285946.jpg", "positive_caption": ["There are exactly 10 pineapples."], "negative_caption": ["There are exactly 9 pineapples."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_285946", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371975.jpg", "positive_caption": ["There are exactly 2 children."], "negative_caption": ["There are exactly 6 children."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371975", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402597.jpg", "positive_caption": ["There are exactly 4 people in the truck."], "negative_caption": ["There are exactly 5 people in the truck."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2402597", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377512.jpg", "positive_caption": ["There are exactly 12 numbers on the clock."], "negative_caption": ["There are exactly 9 numbers on the clock."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377512", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404678.jpg", "positive_caption": ["There are exactly 4 flowers in the vase."], "negative_caption": ["There are exactly 5 flowers in the vase."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2404678", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400911.jpg", "positive_caption": ["There are exactly 4 lamp shades."], "negative_caption": ["There is exactly 1 lamp shade."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400911", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369498.jpg", "positive_caption": ["There are exactly 5 birds above the water."], "negative_caption": ["There is exactly 1 bird above the water."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369498", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374547.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374547", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367108.jpg", "positive_caption": ["There are exactly 2 food trucks pictured."], "negative_caption": ["There are exactly 5 food trucks pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367108", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388191.jpg", "positive_caption": ["There are exactly 6 knobs on the stove."], "negative_caption": ["There are exactly 5 knobs on the stove."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2388191", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368324.jpg", "positive_caption": ["There are exactly 2 elephants."], "negative_caption": ["There is exactly 1 elephant."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368324", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384553.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2384553", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342231.jpg", "positive_caption": ["There are exactly 8 slices shown."], "negative_caption": ["There are exactly 6 slices shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2342231", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378887.jpg", "positive_caption": ["There are exactly 4 men playing."], "negative_caption": ["There are exactly 2 men playing."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2378887", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364632.jpg", "positive_caption": ["1 truck can be seen."], "negative_caption": ["4 trucks can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364632", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366303.jpg", "positive_caption": ["There are exactly 3 total lamps."], "negative_caption": ["There are exactly 0 total lamps."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366303", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377974.jpg", "positive_caption": ["There are exactly 35 lights on the front of this bus."], "negative_caption": ["There is exactly 1 light on the front of this bus."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377974", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373820.jpg", "positive_caption": ["There are exactly 2 electrical wire poles shown."], "negative_caption": ["There is exactly 1 electrical wire pole shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373820", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360501.jpg", "positive_caption": ["7 windows can be seen."], "negative_caption": ["3 windows can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360501", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397338.jpg", "positive_caption": ["There are exactly 0 people pictured."], "negative_caption": ["There are exactly 5 people pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2397338", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370774.jpg", "positive_caption": ["There are exactly 4 planes in the picture."], "negative_caption": ["There are exactly 0 planes in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370774", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364780.jpg", "positive_caption": ["There are exactly 5 people in the photo."], "negative_caption": ["There are exactly 10 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364780", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318826.jpg", "positive_caption": ["There are exactly 7 elephants shown."], "negative_caption": ["There are exactly 2 elephants shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2318826", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372171.jpg", "positive_caption": ["There are exactly 2 people pictured."], "negative_caption": ["There are exactly 4 people pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372171", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375288.jpg", "positive_caption": ["There are exactly 2 people in this picture."], "negative_caption": ["There are exactly 3 people in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375288", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376048.jpg", "positive_caption": ["There are exactly 2 animals in the image."], "negative_caption": ["There is exactly 1 animal in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2376048", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362977.jpg", "positive_caption": ["There is exactly 1 person in this picture."], "negative_caption": ["There are exactly 58 people in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362977", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315553.jpg", "positive_caption": ["There are exactly 6 zebras."], "negative_caption": ["There are exactly 8 zebras."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2315553", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400644.jpg", "positive_caption": ["There are exactly 0 children."], "negative_caption": ["There are exactly 3 children."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400644", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358386.jpg", "positive_caption": ["There are exactly 6 slices left."], "negative_caption": ["There are exactly 4 slices left."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2358386", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401170.jpg", "positive_caption": ["There are exactly 0 cars shown."], "negative_caption": ["There are exactly 4 cars shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401170", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336637.jpg", "positive_caption": ["There are exactly 7 planes in the photo."], "negative_caption": ["There are exactly 6 planes in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2336637", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416706.jpg", "positive_caption": ["There are exactly 0 clouds in the sky."], "negative_caption": ["There are exactly 3 clouds in the sky."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2416706", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1593153.jpg", "positive_caption": ["There are exactly 6 trays of pizza on the counter."], "negative_caption": ["There are exactly 3 trays of pizza on the counter."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1593153", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393648.jpg", "positive_caption": ["There are exactly 5 laptops visible."], "negative_caption": ["There is exactly 1 laptop visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2393648", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367070.jpg", "positive_caption": ["There are exactly 2 lights seen."], "negative_caption": ["There is exactly 1 light seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367070", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352201.jpg", "positive_caption": ["There are exactly 16 rectangles on the garage door."], "negative_caption": ["There are exactly 0 rectangles on the garage door."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2352201", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592049.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592049", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396151.jpg", "positive_caption": ["There are exactly 11 glass bottles in the image."], "negative_caption": ["There are exactly 3 glass bottles in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2396151", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361201.jpg", "positive_caption": ["There is exactly 1 horse."], "negative_caption": ["There are exactly 0 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361201", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413592.jpg", "positive_caption": ["There are exactly 0 of his feet touching the ground."], "negative_caption": ["There is exactly 1 of his feet touching the ground."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2413592", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378568.jpg", "positive_caption": ["There are exactly 0 people pictured here."], "negative_caption": ["There is exactly 1 person pictured here."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2378568", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359392.jpg", "positive_caption": ["There are exactly 2 lights."], "negative_caption": ["There are exactly 3 lights."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359392", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351514.jpg", "positive_caption": ["There are exactly 6 people visibly wearing glasses."], "negative_caption": ["There are exactly 2 people visibly wearing glasses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2351514", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376184.jpg", "positive_caption": ["There are exactly 2 clocks shown."], "negative_caption": ["There are exactly 3 clocks shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2376184", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370812.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370812", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365375.jpg", "positive_caption": ["There are exactly 3 people in the picture."], "negative_caption": ["There are exactly 6 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365375", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383358.jpg", "positive_caption": ["There are exactly 5 men."], "negative_caption": ["There are exactly 2 men."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2383358", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159414.jpg", "positive_caption": ["There are exactly 8 lamps."], "negative_caption": ["There are exactly 6 lamps."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1159414", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373305.jpg", "positive_caption": ["There is exactly 1 mp3 player in the scene."], "negative_caption": ["There are exactly 4 mp3 players in the scene."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373305", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385066.jpg", "positive_caption": ["There are exactly 5 toothbrushes."], "negative_caption": ["There are exactly 4 toothbrushes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2385066", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378459.jpg", "positive_caption": ["There are exactly 3 vehicles in the picture."], "negative_caption": ["There is exactly 1 vehicle in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2378459", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361437.jpg", "positive_caption": ["There are exactly 4 cows shown."], "negative_caption": ["There are exactly 5 cows shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361437", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316827.jpg", "positive_caption": ["There are exactly 8 windows arched at the top."], "negative_caption": ["There are exactly 7 windows arched at the top."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2316827", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387013.jpg", "positive_caption": ["There are exactly 0 people in picture."], "negative_caption": ["There are exactly 11 people in picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2387013", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404901.jpg", "positive_caption": ["There are exactly 6 motorcycles in this photo altogether."], "negative_caption": ["There are exactly 7 motorcycles in this photo altogether."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2404901", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394602.jpg", "positive_caption": ["There are exactly 4 women in the picture."], "negative_caption": ["There are exactly 0 women in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2394602", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370037.jpg", "positive_caption": ["There are exactly 5 bears."], "negative_caption": ["There are exactly 2 bears."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370037", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367531.jpg", "positive_caption": ["There is exactly 1 tub."], "negative_caption": ["There are exactly 2 tubs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367531", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385700.jpg", "positive_caption": ["There are exactly 4 leaves on the pizza."], "negative_caption": ["There are exactly 5 leaves on the pizza."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2385700", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406219.jpg", "positive_caption": ["There are exactly 10 tall trees."], "negative_caption": ["There are exactly 7 tall trees."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2406219", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150327.jpg", "positive_caption": ["There are exactly 3 tall candle holders."], "negative_caption": ["There are exactly 6 tall candle holders."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150327", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398295.jpg", "positive_caption": ["There are exactly 4 cows."], "negative_caption": ["There are exactly 3 cows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2398295", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359385.jpg", "positive_caption": ["There is exactly 1 bulb shown."], "negative_caption": ["There are exactly 3 bulbs shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359385", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159858.jpg", "positive_caption": ["There are exactly 3 men in the picture."], "negative_caption": ["There are exactly 5 men in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1159858", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375581.jpg", "positive_caption": ["There are exactly 6 street signs."], "negative_caption": ["There are exactly 2 street signs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375581", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412204.jpg", "positive_caption": ["There are exactly 4 people seated."], "negative_caption": ["There is exactly 1 person seated."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2412204", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364769.jpg", "positive_caption": ["There is exactly 1 laptop on the table."], "negative_caption": ["There are exactly 0 laptops on the table."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364769", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362298.jpg", "positive_caption": ["There are exactly 2 lights on in the picture."], "negative_caption": ["There are exactly 0 lights on in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362298", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362257.jpg", "positive_caption": ["There is exactly 1 lamp on."], "negative_caption": ["There are exactly 3 lamps on."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362257", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413772.jpg", "positive_caption": ["There are exactly 4 people standing on the tennis court."], "negative_caption": ["There are exactly 2 people standing on the tennis court."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2413772", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377797.jpg", "positive_caption": ["There are exactly 4 horses in the photo."], "negative_caption": ["There are exactly 2 horses in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377797", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362189.jpg", "positive_caption": ["There are exactly 3 pictures hanging above the TV."], "negative_caption": ["There are exactly 0 pictures hanging above the TV."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362189", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368862.jpg", "positive_caption": ["There is exactly 1 horse."], "negative_caption": ["There are exactly 5 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368862", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368708.jpg", "positive_caption": ["There are exactly 2 elephants shown."], "negative_caption": ["There are exactly 0 elephants shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368708", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370136.jpg", "positive_caption": ["There is exactly 1 motorcycle in the photo."], "negative_caption": ["There are exactly 2 motorcycles in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370136", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374260.jpg", "positive_caption": ["There are exactly 2 street signs showing."], "negative_caption": ["There are exactly 4 street signs showing."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374260", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368913.jpg", "positive_caption": ["There are exactly 3 stand alone monitors."], "negative_caption": ["There are exactly 0 stand alone monitors."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368913", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370603.jpg", "positive_caption": ["There is exactly 1 bird in the picture."], "negative_caption": ["There are exactly 0 birds in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370603", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407094.jpg", "positive_caption": ["There are exactly 10 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2407094", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285977.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_285977", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150518.jpg", "positive_caption": ["There are exactly 3 men standing in front of the elephant."], "negative_caption": ["There are exactly 5 men standing in front of the elephant."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150518", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396082.jpg", "positive_caption": ["8 windows can be seen on the church."], "negative_caption": ["9 windows can be seen on the church."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2396082", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359865.jpg", "positive_caption": ["There are exactly 0 people on the track."], "negative_caption": ["There are exactly 5 people on the track."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359865", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370549.jpg", "positive_caption": ["There are exactly 2 giraffes in the picture."], "negative_caption": ["There are exactly 5 giraffes in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370549", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390364.jpg", "positive_caption": ["There are exactly 5 objects on the mantle."], "negative_caption": ["There are exactly 2 objects on the mantle."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2390364", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339046.jpg", "positive_caption": ["There are exactly 5 poles visible."], "negative_caption": ["There are exactly 7 poles visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2339046", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316187.jpg", "positive_caption": ["There are exactly 9 people."], "negative_caption": ["There are exactly 4 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2316187", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382317.jpg", "positive_caption": ["There are exactly 5 children."], "negative_caption": ["There are exactly 9 children."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2382317", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398455.jpg", "positive_caption": ["There are exactly 4 players."], "negative_caption": ["There are exactly 5 players."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2398455", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374397.jpg", "positive_caption": ["There are exactly 2 people in image."], "negative_caption": ["There are exactly 3 people in image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374397", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360065.jpg", "positive_caption": ["There is exactly 1 man."], "negative_caption": ["There are exactly 3 men."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360065", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372813.jpg", "positive_caption": ["There are exactly 3 people on the field."], "negative_caption": ["There are exactly 6 people on the field."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372813", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363950.jpg", "positive_caption": ["You can distinguish 0 people's faces."], "negative_caption": ["You can distinguish 1 person's faces."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363950", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370191.jpg", "positive_caption": ["There are exactly 0 women in this picture."], "negative_caption": ["There are exactly 6 women in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370191", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366811.jpg", "positive_caption": ["There are exactly 3 tables."], "negative_caption": ["There is exactly 1 table."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366811", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159346.jpg", "positive_caption": ["There are exactly 3 pizzas in in front of the window."], "negative_caption": ["There are exactly 2 pizzas in in front of the window."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1159346", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400920.jpg", "positive_caption": ["There are exactly 0 dinosaurs in the picture."], "negative_caption": ["There is exactly 1 dinosaur in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400920", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383699.jpg", "positive_caption": ["There are exactly 0 people visible."], "negative_caption": ["There is exactly 1 person visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2383699", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592158.jpg", "positive_caption": ["There are exactly 6 women under the umbrella."], "negative_caption": ["There are exactly 7 women under the umbrella."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592158", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374520.jpg", "positive_caption": ["There are exactly 5 people at the table."], "negative_caption": ["There are exactly 4 people at the table."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374520", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400586.jpg", "positive_caption": ["There are exactly 21 children."], "negative_caption": ["There are exactly 3 children."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400586", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592887.jpg", "positive_caption": ["There are exactly 3 trucks."], "negative_caption": ["There are exactly 4 trucks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592887", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404437.jpg", "positive_caption": ["There are exactly 14 umbrellas in the picture."], "negative_caption": ["There is exactly 1 umbrella in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2404437", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403198.jpg", "positive_caption": ["There are exactly 6 males pictured."], "negative_caption": ["There are exactly 0 males pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403198", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373024.jpg", "positive_caption": ["There is exactly 1 person in this photo."], "negative_caption": ["There are exactly 0 people in this photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373024", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373190.jpg", "positive_caption": ["There are exactly 0 dogs in the picture."], "negative_caption": ["There are exactly 3 dogs in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373190", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379053.jpg", "positive_caption": ["There are exactly 6 people visible."], "negative_caption": ["There are exactly 5 people visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2379053", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416837.jpg", "positive_caption": ["There are exactly 0 dinosaurs in the picture."], "negative_caption": ["There are exactly 12 dinosaurs in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2416837", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405539.jpg", "positive_caption": ["There are exactly 5 zebras in the photo."], "negative_caption": ["There are exactly 2 zebras in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2405539", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364288.jpg", "positive_caption": ["There are exactly 2 legs of the zebra."], "negative_caption": ["There are exactly 3 legs of the zebra."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364288", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361175.jpg", "positive_caption": ["There are exactly 4 windows and doors."], "negative_caption": ["There are exactly 6 windows and doors."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361175", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389077.jpg", "positive_caption": ["There are exactly 5 lights above the mirror."], "negative_caption": ["There are exactly 3 lights above the mirror."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2389077", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370710.jpg", "positive_caption": ["There are exactly 2 types of pavers."], "negative_caption": ["There is exactly 1 type of paver."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370710", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361742.jpg", "positive_caption": ["There are exactly 8 boats."], "negative_caption": ["There is exactly 1 boat."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361742", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377701.jpg", "positive_caption": ["There are exactly 3 vases."], "negative_caption": ["There is exactly 1 vase."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377701", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401034.jpg", "positive_caption": ["There are exactly 5 people in the picture."], "negative_caption": ["There are exactly 6 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401034", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371746.jpg", "positive_caption": ["There are exactly 2 wheels."], "negative_caption": ["There are exactly 3 wheels."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371746", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340393.jpg", "positive_caption": ["There are exactly 5 surfboards shown."], "negative_caption": ["There are exactly 4 surfboards shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2340393", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373612.jpg", "positive_caption": ["There are exactly 2 people in the photo."], "negative_caption": ["There are exactly 0 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373612", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416630.jpg", "positive_caption": ["There are exactly 5 images of the men displayed."], "negative_caption": ["There are exactly 3 images of the men displayed."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2416630", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378957.jpg", "positive_caption": ["There are exactly 5 people in the picture."], "negative_caption": ["There are exactly 0 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2378957", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371874.jpg", "positive_caption": ["There is exactly 1 pizza."], "negative_caption": ["There are exactly 3 pizzas."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371874", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318628.jpg", "positive_caption": ["There are exactly 15 bears."], "negative_caption": ["There are exactly 0 bears."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2318628", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363361.jpg", "positive_caption": ["There are exactly 2 people playing baseball."], "negative_caption": ["There are exactly 5 people playing baseball."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363361", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371124.jpg", "positive_caption": ["There are exactly 2 kids shown."], "negative_caption": ["There are exactly 6 kids shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371124", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363723.jpg", "positive_caption": ["There are exactly 2 lights on the sides of the bed."], "negative_caption": ["There is exactly 1 light on the sides of the bed."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363723", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378084.jpg", "positive_caption": ["There are exactly 4 elephants."], "negative_caption": ["There is exactly 1 elephant."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2378084", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713229.jpg", "positive_caption": ["There are exactly 4 doors on the smaller airplane."], "negative_caption": ["There are exactly 0 doors on the smaller airplane."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_713229", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387440.jpg", "positive_caption": ["There are exactly 0 humans in the picture."], "negative_caption": ["There are exactly 2 humans in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2387440", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410238.jpg", "positive_caption": ["There are exactly 5 tables visible."], "negative_caption": ["There are exactly 2 tables visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2410238", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356935.jpg", "positive_caption": ["There are exactly 9 flowers."], "negative_caption": ["There are exactly 12 flowers."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2356935", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376176.jpg", "positive_caption": ["There are exactly 3 pieces."], "negative_caption": ["There are exactly 8 pieces."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2376176", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372572.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372572", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369494.jpg", "positive_caption": ["There are exactly 2 elephant trunks."], "negative_caption": ["There are exactly 3 elephant trunks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369494", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342923.jpg", "positive_caption": ["There are exactly 7 letters on the license plate."], "negative_caption": ["There are exactly 6 letters on the license plate."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2342923", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359816.jpg", "positive_caption": ["2 bananas can be seen."], "negative_caption": ["6 bananas can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359816", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337962.jpg", "positive_caption": ["There are exactly 5 players."], "negative_caption": ["There are exactly 3 players."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2337962", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361004.jpg", "positive_caption": ["There are exactly 5 players."], "negative_caption": ["There are exactly 6 players."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361004", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342902.jpg", "positive_caption": ["There are exactly 5 people in the image."], "negative_caption": ["There are exactly 2 people in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2342902", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367895.jpg", "positive_caption": ["There is exactly 1 bicycle."], "negative_caption": ["There are exactly 0 bicycles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367895", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381619.jpg", "positive_caption": ["There are exactly 7 horses."], "negative_caption": ["There are exactly 0 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381619", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370419.jpg", "positive_caption": ["There are exactly 3 tree trunks shown."], "negative_caption": ["There are exactly 9 tree trunks shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370419", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399514.jpg", "positive_caption": ["There are exactly 0 cows walking on the mountains."], "negative_caption": ["There are exactly 2 cows walking on the mountains."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2399514", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319151.jpg", "positive_caption": ["There are exactly 5 ears shown in the picture."], "negative_caption": ["There are exactly 2 ears shown in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2319151", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413285.jpg", "positive_caption": ["There are exactly 6 remotes."], "negative_caption": ["There are exactly 8 remotes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2413285", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360379.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 7 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360379", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362122.jpg", "positive_caption": ["There are exactly 3 windows at the front of the larger boat."], "negative_caption": ["There is exactly 1 window at the front of the larger boat."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362122", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150543.jpg", "positive_caption": ["There are exactly 3 windows shown."], "negative_caption": ["There are exactly 2 windows shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150543", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387063.jpg", "positive_caption": ["There are exactly 4 people here."], "negative_caption": ["There are exactly 3 people here."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2387063", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402653.jpg", "positive_caption": ["There are exactly 4 glasses in the photo."], "negative_caption": ["There are exactly 3 glasses in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2402653", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360550.jpg", "positive_caption": ["There is exactly 1 walking sign shown."], "negative_caption": ["There are exactly 2 walking signs shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360550", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337724.jpg", "positive_caption": ["There are exactly 6 giraffes."], "negative_caption": ["There are exactly 5 giraffes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2337724", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338184.jpg", "positive_caption": ["There are exactly 10 pieces of fruit."], "negative_caption": ["There are exactly 12 pieces of fruit."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2338184", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324837.jpg", "positive_caption": ["There are exactly 6 cameras in the window."], "negative_caption": ["There are exactly 2 cameras in the window."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2324837", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391470.jpg", "positive_caption": ["There are exactly 5 umbrellas open."], "negative_caption": ["There are exactly 2 umbrellas open."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2391470", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396742.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2396742", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403679.jpg", "positive_caption": ["There are exactly 6 cell phones on the red tray."], "negative_caption": ["There are exactly 5 cell phones on the red tray."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403679", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374652.jpg", "positive_caption": ["There are exactly 2 signs on the building."], "negative_caption": ["There is exactly 1 sign on the building."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374652", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365558.jpg", "positive_caption": ["There are exactly 3 traffic lights pictured."], "negative_caption": ["There are exactly 9 traffic lights pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365558", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411229.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2411229", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368931.jpg", "positive_caption": ["There are exactly 4 planes in the picture."], "negative_caption": ["There are exactly 5 planes in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368931", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360440.jpg", "positive_caption": ["There are exactly 3 bears."], "negative_caption": ["There are exactly 4 bears."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360440", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371925.jpg", "positive_caption": ["There is exactly 1 lamp."], "negative_caption": ["There are exactly 2 lamps."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371925", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150498.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 8 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150498", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401288.jpg", "positive_caption": ["There are exactly 0 people pictured here."], "negative_caption": ["There are exactly 2 people pictured here."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401288", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316217.jpg", "positive_caption": ["There are exactly 6 logs on the bottom row."], "negative_caption": ["There are exactly 2 logs on the bottom row."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2316217", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394950.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2394950", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359483.jpg", "positive_caption": ["There is exactly 1 cat."], "negative_caption": ["There are exactly 4 cats."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359483", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391208.jpg", "positive_caption": ["There are exactly 4 zebras in the picture."], "negative_caption": ["There are exactly 13 zebras in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2391208", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338716.jpg", "positive_caption": ["There are exactly 6 people in the picture."], "negative_caption": ["There are exactly 5 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2338716", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372786.jpg", "positive_caption": ["There are exactly 4 plates shown."], "negative_caption": ["There is exactly 1 plate shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372786", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376638.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2376638", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361244.jpg", "positive_caption": ["There are exactly 4 zebras in photo."], "negative_caption": ["There are exactly 6 zebras in photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361244", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346784.jpg", "positive_caption": ["There are exactly 12 numbers on the clock."], "negative_caption": ["There are exactly 10 numbers on the clock."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2346784", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591825.jpg", "positive_caption": ["There are exactly 15 kids in the pictures."], "negative_caption": ["There is exactly 1 kid in the pictures."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591825", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400857.jpg", "positive_caption": ["There are exactly 4 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400857", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365956.jpg", "positive_caption": ["There are exactly 3 pendent lights showing."], "negative_caption": ["There are exactly 6 pendent lights showing."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365956", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365932.jpg", "positive_caption": ["There is exactly 1 person shown."], "negative_caption": ["There are exactly 4 people shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365932", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389272.jpg", "positive_caption": ["There are exactly 7 cows."], "negative_caption": ["There are exactly 3 cows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2389272", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285805.jpg", "positive_caption": ["There are exactly 0 clouds visible in the sky."], "negative_caption": ["There are exactly 7 clouds visible in the sky."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_285805", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387414.jpg", "positive_caption": ["There are exactly 4 tires."], "negative_caption": ["There are exactly 12 tires."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2387414", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400879.jpg", "positive_caption": ["There are exactly 0 horses."], "negative_caption": ["There are exactly 6 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400879", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375204.jpg", "positive_caption": ["There are exactly 6 statues shown."], "negative_caption": ["There are exactly 3 statues shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375204", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159282.jpg", "positive_caption": ["There are exactly 9 windows in the door."], "negative_caption": ["There is exactly 1 window in the door."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1159282", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326613.jpg", "positive_caption": ["There are exactly 5 poles visible on the building."], "negative_caption": ["There are exactly 2 poles visible on the building."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2326613", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318842.jpg", "positive_caption": ["There are exactly 8 knobs visible."], "negative_caption": ["There are exactly 0 knobs visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2318842", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150406.jpg", "positive_caption": ["5 tables can be seen."], "negative_caption": ["6 tables can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150406", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395930.jpg", "positive_caption": ["There are exactly 0 people shown."], "negative_caption": ["There is exactly 1 person shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2395930", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371885.jpg", "positive_caption": ["There is exactly 1 person visible."], "negative_caption": ["There are exactly 5 people visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371885", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331474.jpg", "positive_caption": ["There are exactly 6 people in this picture."], "negative_caption": ["There are exactly 0 people in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2331474", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358026.jpg", "positive_caption": ["There are exactly 6 windows shown from the building at the bottom."], "negative_caption": ["There are exactly 3 windows shown from the building at the bottom."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2358026", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370020.jpg", "positive_caption": ["There are exactly 2 clear lights on the front of the train."], "negative_caption": ["There is exactly 1 clear light on the front of the train."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370020", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350013.jpg", "positive_caption": ["There are exactly 6 umbrellas pictured."], "negative_caption": ["There are exactly 3 umbrellas pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2350013", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383309.jpg", "positive_caption": ["There are exactly 0 people in the tub."], "negative_caption": ["There are exactly 2 people in the tub."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2383309", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1160223.jpg", "positive_caption": ["There are exactly 30 miles per hour permitted on the street during normal day hours."], "negative_caption": ["There are exactly 35 miles per hour permitted on the street during normal day hours."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1160223", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373777.jpg", "positive_caption": ["There are exactly 2 people playing."], "negative_caption": ["There are exactly 4 people playing."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373777", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361449.jpg", "positive_caption": ["There are exactly 3 trees clearly visible."], "negative_caption": ["There are exactly 5 trees clearly visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361449", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370734.jpg", "positive_caption": ["There is exactly 1 plane."], "negative_caption": ["There are exactly 4 planes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370734", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372059.jpg", "positive_caption": ["There are exactly 2 shoes on the skateboard."], "negative_caption": ["There are exactly 3 shoes on the skateboard."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372059", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327539.jpg", "positive_caption": ["There are exactly 5 toothbrushes in the photo."], "negative_caption": ["There are exactly 2 toothbrushes in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2327539", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357138.jpg", "positive_caption": ["There are exactly 5 lemon slices."], "negative_caption": ["There are exactly 8 lemon slices."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2357138", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361951.jpg", "positive_caption": ["There is exactly 1 train in this picture."], "negative_caption": ["There are exactly 4 trains in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361951", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330058.jpg", "positive_caption": ["There are exactly 7 giraffes in the picture."], "negative_caption": ["There are exactly 0 giraffes in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2330058", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372302.jpg", "positive_caption": ["There are exactly 3 pieces of decorative tile in the picture."], "negative_caption": ["There are exactly 0 pieces of decorative tile in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372302", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398034.jpg", "positive_caption": ["There are exactly 4 stars on flag."], "negative_caption": ["There are exactly 10 stars on flag."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2398034", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380419.jpg", "positive_caption": ["There are exactly 3 cows in the picture."], "negative_caption": ["There are exactly 4 cows in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2380419", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392254.jpg", "positive_caption": ["There are exactly 6 boats visible in this photo."], "negative_caption": ["There is exactly 1 boat visible in this photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2392254", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403594.jpg", "positive_caption": ["There are exactly 4 cows."], "negative_caption": ["There are exactly 12 cows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403594", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367084.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 0 giraffe."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367084", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372332.jpg", "positive_caption": ["There are exactly 5 people in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372332", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369922.jpg", "positive_caption": ["There are exactly 2 doors on the fridge."], "negative_caption": ["There is exactly 1 door on the fridge."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369922", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361222.jpg", "positive_caption": ["There is exactly 1 skier."], "negative_caption": ["There are exactly 5 skiers."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361222", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380733.jpg", "positive_caption": ["There are exactly 3 plates shown."], "negative_caption": ["There are exactly 6 plates shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2380733", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354114.jpg", "positive_caption": ["There are exactly 10 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2354114", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405906.jpg", "positive_caption": ["There are exactly 4 animals total."], "negative_caption": ["There are exactly 3 animals total."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2405906", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375625.jpg", "positive_caption": ["There are exactly 2 visible drawer handles."], "negative_caption": ["There are exactly 6 visible drawer handles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375625", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366034.jpg", "positive_caption": ["There are exactly 4 pillows."], "negative_caption": ["There are exactly 12 pillows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366034", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381418.jpg", "positive_caption": ["There are exactly 3 soccer players."], "negative_caption": ["There are exactly 5 soccer players."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381418", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415103.jpg", "positive_caption": ["There are exactly 8 people were in the picture."], "negative_caption": ["There are exactly 0 people were in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2415103", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345435.jpg", "positive_caption": ["There are exactly 10 poles."], "negative_caption": ["There are exactly 2 poles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2345435", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376329.jpg", "positive_caption": ["There are exactly 6 yellow flowers."], "negative_caption": ["There are exactly 2 yellow flowers."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2376329", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373129.jpg", "positive_caption": ["5 people can be seen."], "negative_caption": ["0 people can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373129", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392217.jpg", "positive_caption": ["There are exactly 4 people standing on the stone surface in the foreground of the photo."], "negative_caption": ["There are exactly 3 people standing on the stone surface in the foreground of the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2392217", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333955.jpg", "positive_caption": ["There are exactly 10 people."], "negative_caption": ["There are exactly 4 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2333955", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363610.jpg", "positive_caption": ["There is exactly 1 plane."], "negative_caption": ["There are exactly 2 planes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363610", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370926.jpg", "positive_caption": ["There is exactly 1 player visible."], "negative_caption": ["There are exactly 3 players visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370926", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370238.jpg", "positive_caption": ["There are exactly 3 cars."], "negative_caption": ["There are exactly 12 cars."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370238", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380111.jpg", "positive_caption": ["There are exactly 3 men shown."], "negative_caption": ["There are exactly 7 men shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2380111", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395433.jpg", "positive_caption": ["There are exactly 8 books pictured."], "negative_caption": ["There are exactly 0 books pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2395433", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370947.jpg", "positive_caption": ["There is exactly 1 animal in the photo."], "negative_caption": ["There are exactly 0 animals in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370947", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381615.jpg", "positive_caption": ["There are exactly 6 players shown."], "negative_caption": ["There are exactly 8 players shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381615", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374510.jpg", "positive_caption": ["There are exactly 8 different items in the picture."], "negative_caption": ["There are exactly 10 different items in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374510", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713697.jpg", "positive_caption": ["There are exactly 5 people in the photo."], "negative_caption": ["There are exactly 6 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_713697", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359936.jpg", "positive_caption": ["There are exactly 2 zebras visible."], "negative_caption": ["There are exactly 3 zebras visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359936", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369286.jpg", "positive_caption": ["There is exactly 1 zebra."], "negative_caption": ["There are exactly 0 zebras."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369286", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375061.jpg", "positive_caption": ["You see exactly 4 heads."], "negative_caption": ["You see exactly 5 heads."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375061", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362172.jpg", "positive_caption": ["There are exactly 2 signs."], "negative_caption": ["There are exactly 3 signs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362172", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369351.jpg", "positive_caption": ["There are exactly 5 cows looking at the camera."], "negative_caption": ["There is exactly 1 cow looking at the camera."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369351", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373248.jpg", "positive_caption": ["There are exactly 2 men in the picture."], "negative_caption": ["There are exactly 5 men in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373248", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368929.jpg", "positive_caption": ["There are exactly 2 animals."], "negative_caption": ["There are exactly 7 animals."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368929", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363200.jpg", "positive_caption": ["There is exactly 1 sliced."], "negative_caption": ["There are exactly 2 sliced."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363200", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390572.jpg", "positive_caption": ["There are exactly 5 people pictured."], "negative_caption": ["There are exactly 2 people pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2390572", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592835.jpg", "positive_caption": ["There are exactly 4 chairs."], "negative_caption": ["There is exactly 1 chair."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592835", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373889.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There are exactly 6 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373889", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370788.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370788", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383311.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 4 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2383311", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364521.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 0 giraffes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364521", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360441.jpg", "positive_caption": ["There are exactly 2 buses."], "negative_caption": ["There are exactly 5 buses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360441", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381178.jpg", "positive_caption": ["There are exactly 4 signs on the post."], "negative_caption": ["There are exactly 6 signs on the post."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381178", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409923.jpg", "positive_caption": ["There are exactly 7 people in the room."], "negative_caption": ["There are exactly 5 people in the room."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2409923", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404285.jpg", "positive_caption": ["There are exactly 4 kids."], "negative_caption": ["There are exactly 20 kids."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2404285", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365064.jpg", "positive_caption": ["There are exactly 2 sinks."], "negative_caption": ["There are exactly 3 sinks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365064", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368327.jpg", "positive_caption": ["There are exactly 2 man."], "negative_caption": ["There is exactly 1 man."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368327", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365399.jpg", "positive_caption": ["There is exactly 1 train shown."], "negative_caption": ["There are exactly 4 trains shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365399", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372856.jpg", "positive_caption": ["1 of the man of have hats."], "negative_caption": ["4 of the men of have hats."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372856", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390727.jpg", "positive_caption": ["There are exactly 0 animals."], "negative_caption": ["There are exactly 8 animals."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2390727", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159800.jpg", "positive_caption": ["There are exactly 5 people on the boat."], "negative_caption": ["There are exactly 3 people on the boat."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1159800", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366825.jpg", "positive_caption": ["There are exactly 2 light poles in the photo."], "negative_caption": ["There are exactly 3 light poles in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366825", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403149.jpg", "positive_caption": ["There are exactly 0 people pictured here."], "negative_caption": ["There are exactly 3 people pictured here."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403149", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364740.jpg", "positive_caption": ["There are exactly 2 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364740", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371067.jpg", "positive_caption": ["There is exactly 1 skater."], "negative_caption": ["There are exactly 2 skaters."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371067", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374237.jpg", "positive_caption": ["There are exactly 0 people riding the horses."], "negative_caption": ["There are exactly 2 people riding the horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374237", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338486.jpg", "positive_caption": ["There are exactly 13 windows in the white building."], "negative_caption": ["There are exactly 8 windows in the white building."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2338486", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374311.jpg", "positive_caption": ["There are exactly 7 lights on the ceiling."], "negative_caption": ["There are exactly 2 lights on the ceiling."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374311", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413823.jpg", "positive_caption": ["There are exactly 7 buses."], "negative_caption": ["There are exactly 5 buses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2413823", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374119.jpg", "positive_caption": ["There is exactly 1 cat."], "negative_caption": ["There are exactly 2 cats."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374119", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285996.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_285996", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373297.jpg", "positive_caption": ["There are exactly 7 umbrellas in the picture."], "negative_caption": ["There are exactly 0 umbrellas in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373297", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360933.jpg", "positive_caption": ["There are exactly 4 floor grates visible."], "negative_caption": ["There are exactly 5 floor grates visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360933", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362052.jpg", "positive_caption": ["There are exactly 9 squares on the window."], "negative_caption": ["There are exactly 10 squares on the window."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362052", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361872.jpg", "positive_caption": ["There are exactly 3 wheels visible on the plane."], "negative_caption": ["There are exactly 4 wheels visible on the plane."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361872", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369640.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369640", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368470.jpg", "positive_caption": ["There are exactly 3 bananas."], "negative_caption": ["There are exactly 4 bananas."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368470", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368996.jpg", "positive_caption": ["There are exactly 2 eyes of the bird in the photo."], "negative_caption": ["There are exactly 0 eyes of the bird in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368996", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382393.jpg", "positive_caption": ["There are exactly 3 broccoli florets visible."], "negative_caption": ["There is exactly 1 broccoli floret visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2382393", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319783.jpg", "positive_caption": ["There are exactly 8 traffic lights in the picture."], "negative_caption": ["There are exactly 6 traffic lights in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2319783", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369147.jpg", "positive_caption": ["There is exactly 1 snowman in the picture."], "negative_caption": ["There are exactly 2 snowmen in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369147", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415100.jpg", "positive_caption": ["There are exactly 7 yellow stripes on the street."], "negative_caption": ["There are exactly 6 yellow stripes on the street."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2415100", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363971.jpg", "positive_caption": ["There are exactly 4 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363971", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323770.jpg", "positive_caption": ["There are exactly 5 lemons."], "negative_caption": ["There are exactly 0 lemons."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2323770", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1593091.jpg", "positive_caption": ["There are exactly 6 chairs."], "negative_caption": ["There are exactly 4 chairs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1593091", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364353.jpg", "positive_caption": ["There are exactly 3 people."], "negative_caption": ["There are exactly 6 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364353", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366398.jpg", "positive_caption": ["There are exactly 2 junk trucks."], "negative_caption": ["There are exactly 3 junk trucks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366398", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406500.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2406500", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592377.jpg", "positive_caption": ["There are exactly 3 motorscyles."], "negative_caption": ["There is exactly 1 motorscyle."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592377", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373273.jpg", "positive_caption": ["They are exactly 1."], "negative_caption": ["They are exactly 0."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373273", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373560.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 5 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373560", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365081.jpg", "positive_caption": ["There are exactly 2 planes in the picture."], "negative_caption": ["There are exactly 7 planes in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365081", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400372.jpg", "positive_caption": ["There are exactly 6 chairs in the image."], "negative_caption": ["There are exactly 4 chairs in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400372", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407966.jpg", "positive_caption": ["There are exactly 9 people in this picture."], "negative_caption": ["There are exactly 0 people in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2407966", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390942.jpg", "positive_caption": ["You see exactly 0 people."], "negative_caption": ["You see exactly 12 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2390942", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377002.jpg", "positive_caption": ["There are exactly 3 mountain goats pictured."], "negative_caption": ["There are exactly 2 mountain goats pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377002", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592325.jpg", "positive_caption": ["There are exactly 4 red lights on."], "negative_caption": ["There are exactly 2 red lights on."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592325", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359945.jpg", "positive_caption": ["There are exactly 2 power lines pictured."], "negative_caption": ["There are exactly 5 power lines pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359945", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384229.jpg", "positive_caption": ["There are exactly 6 people in the scene."], "negative_caption": ["There are exactly 4 people in the scene."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2384229", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592431.jpg", "positive_caption": ["There are exactly 3 people in the picture."], "negative_caption": ["There are exactly 4 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592431", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360961.jpg", "positive_caption": ["There are exactly 4 cars."], "negative_caption": ["There are exactly 0 cars."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360961", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404184.jpg", "positive_caption": ["There are exactly 7 people on the boat."], "negative_caption": ["There are exactly 5 people on the boat."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2404184", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327349.jpg", "positive_caption": ["There are exactly 10 soda cans shown."], "negative_caption": ["There are exactly 8 soda cans shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2327349", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388051.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2388051", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407637.jpg", "positive_caption": ["There are exactly 7 white stripes on the street."], "negative_caption": ["There are exactly 5 white stripes on the street."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2407637", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373565.jpg", "positive_caption": ["There are exactly 2 men in the scene."], "negative_caption": ["There are exactly 0 men in the scene."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373565", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591944.jpg", "positive_caption": ["There are exactly 3 wheels."], "negative_caption": ["There are exactly 4 wheels."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591944", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592053.jpg", "positive_caption": ["There are exactly 3 pairs of scissors."], "negative_caption": ["There are exactly 4 pairs of scissors."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592053", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372053.jpg", "positive_caption": ["There is exactly 1 refrigerator."], "negative_caption": ["There are exactly 2 refrigerators."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372053", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406711.jpg", "positive_caption": ["There are exactly 5 flip phones."], "negative_caption": ["There are exactly 0 flip phones."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2406711", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347700.jpg", "positive_caption": ["There are exactly 8 slices."], "negative_caption": ["There are exactly 3 slices."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2347700", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414892.jpg", "positive_caption": ["There are exactly 8 slices of pizza."], "negative_caption": ["There are exactly 0 slices of pizza."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2414892", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364790.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 9 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364790", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412097.jpg", "positive_caption": ["There are exactly 5 sheep."], "negative_caption": ["There are exactly 8 sheep."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2412097", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381738.jpg", "positive_caption": ["There are exactly 3 forks."], "negative_caption": ["There are exactly 2 forks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381738", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374590.jpg", "positive_caption": ["There are exactly 3 garage doors present."], "negative_caption": ["There is exactly 1 garage door present."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374590", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414988.jpg", "positive_caption": ["There are exactly 4 tusks visible."], "negative_caption": ["There are exactly 3 tusks visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2414988", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395590.jpg", "positive_caption": ["There are exactly 6 pillows."], "negative_caption": ["There is exactly 1 pillow."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2395590", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391215.jpg", "positive_caption": ["There are exactly 0 people in picture."], "negative_caption": ["There is exactly 1 person in picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2391215", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397902.jpg", "positive_caption": ["There are exactly 18 sections make up the doors and border of doors."], "negative_caption": ["There are exactly 4 sections make up the doors and border of doors."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2397902", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362436.jpg", "positive_caption": ["There is exactly 1 pizza."], "negative_caption": ["There are exactly 2 pizzas."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362436", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416742.jpg", "positive_caption": ["There are exactly 4 people visible."], "negative_caption": ["There are exactly 6 people visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2416742", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352946.jpg", "positive_caption": ["There are exactly 5 cows."], "negative_caption": ["There are exactly 9 cows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2352946", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362750.jpg", "positive_caption": ["There is exactly 1 person pictured."], "negative_caption": ["There are exactly 3 people pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362750", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377056.jpg", "positive_caption": ["There are exactly 3 police officers."], "negative_caption": ["There is exactly 1 police officer."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377056", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370167.jpg", "positive_caption": ["There are exactly 3 trains in this image."], "negative_caption": ["There are exactly 4 trains in this image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370167", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366355.jpg", "positive_caption": ["3 people with sheep have white coats."], "negative_caption": ["2 people with sheep have white coats."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366355", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367094.jpg", "positive_caption": ["There are exactly 2 children."], "negative_caption": ["There is exactly 1 child."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367094", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407816.jpg", "positive_caption": ["There are exactly 4 planes."], "negative_caption": ["There are exactly 6 planes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2407816", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368246.jpg", "positive_caption": ["There is exactly 1 motorcycle in the photo."], "negative_caption": ["There are exactly 5 motorcycles in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368246", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361375.jpg", "positive_caption": ["There are exactly 4 people in this picture."], "negative_caption": ["There are exactly 12 people in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361375", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369436.jpg", "positive_caption": ["There are exactly 2 umbrellas in the image."], "negative_caption": ["There are exactly 4 umbrellas in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369436", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386605.jpg", "positive_caption": ["4 people can be seen on the bus."], "negative_caption": ["2 people can be seen on the bus."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2386605", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402688.jpg", "positive_caption": ["There are exactly 5 flower buds."], "negative_caption": ["There are exactly 3 flower buds."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2402688", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389920.jpg", "positive_caption": ["There are exactly 9 people shown."], "negative_caption": ["There are exactly 3 people shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2389920", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361671.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 6 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361671", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366276.jpg", "positive_caption": ["There is exactly 1 person shown."], "negative_caption": ["There are exactly 4 people shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366276", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592895.jpg", "positive_caption": ["There are exactly 0 cars on the street."], "negative_caption": ["There are exactly 3 cars on the street."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592895", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319378.jpg", "positive_caption": ["There are exactly 7 people present."], "negative_caption": ["There are exactly 9 people present."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2319378", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332684.jpg", "positive_caption": ["There are exactly 8 chairs at the dining table."], "negative_caption": ["There are exactly 4 chairs at the dining table."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2332684", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338274.jpg", "positive_caption": ["There are exactly 5 animals visible."], "negative_caption": ["There are exactly 2 animals visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2338274", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320226.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2320226", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591982.jpg", "positive_caption": ["There are exactly 8 pillows total between the two couches."], "negative_caption": ["There are exactly 5 pillows total between the two couches."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591982", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328805.jpg", "positive_caption": ["There are exactly 5 trucks visible."], "negative_caption": ["There are exactly 14 trucks visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2328805", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325142.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2325142", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399357.jpg", "positive_caption": ["There are exactly 4 animals in all."], "negative_caption": ["There are exactly 3 animals in all."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2399357", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366224.jpg", "positive_caption": ["There is exactly 1 pair of scissors in the picture."], "negative_caption": ["There are exactly 4 pairs of scissors in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366224", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370390.jpg", "positive_caption": ["There are exactly 2 kites."], "negative_caption": ["There are exactly 14 kites."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370390", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381725.jpg", "positive_caption": ["4 fingers can be seen in the picture."], "negative_caption": ["1 finger can be seen in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381725", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360050.jpg", "positive_caption": ["There is exactly 1 train in the picture."], "negative_caption": ["There are exactly 2 trains in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360050", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591818.jpg", "positive_caption": ["There are exactly 3 bicycles."], "negative_caption": ["There are exactly 2 bicycles."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591818", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374607.jpg", "positive_caption": ["There are exactly 4 people in this image."], "negative_caption": ["There are exactly 6 people in this image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374607", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370873.jpg", "positive_caption": ["There are exactly 4 plates shown in the photo."], "negative_caption": ["There are exactly 14 plates shown in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370873", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159509.jpg", "positive_caption": ["There are exactly 6 mugs stacked on top of one another."], "negative_caption": ["There are exactly 4 mugs stacked on top of one another."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1159509", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360027.jpg", "positive_caption": ["There are exactly 2 children."], "negative_caption": ["There are exactly 0 children."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360027", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355746.jpg", "positive_caption": ["There are exactly 6 lights in the room."], "negative_caption": ["There are exactly 8 lights in the room."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2355746", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414180.jpg", "positive_caption": ["There are exactly 4 people in the image."], "negative_caption": ["There are exactly 8 people in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2414180", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_107913.jpg", "positive_caption": ["There are exactly 8 sticks."], "negative_caption": ["There are exactly 7 sticks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_107913", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372280.jpg", "positive_caption": ["There are exactly 7 skis."], "negative_caption": ["There are exactly 8 skis."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372280", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380672.jpg", "positive_caption": ["There are exactly 3 small buildings."], "negative_caption": ["There are exactly 5 small buildings."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2380672", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352424.jpg", "positive_caption": ["There are exactly 12 windows visible."], "negative_caption": ["There are exactly 2 windows visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2352424", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398466.jpg", "positive_caption": ["There are exactly 4 vehicles total visible."], "negative_caption": ["There are exactly 6 vehicles total visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2398466", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405117.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2405117", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375472.jpg", "positive_caption": ["There are exactly 2 blocks of ice."], "negative_caption": ["There are exactly 10 blocks of ice."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375472", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360971.jpg", "positive_caption": ["There are exactly 3 people in the picture."], "negative_caption": ["There are exactly 8 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360971", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375642.jpg", "positive_caption": ["There are exactly 4 people visible."], "negative_caption": ["There are exactly 3 people visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375642", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1593022.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1593022", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403870.jpg", "positive_caption": ["There are exactly 0 people shown."], "negative_caption": ["There is exactly 1 person shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403870", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353138.jpg", "positive_caption": ["There are exactly 6 words total on the sign."], "negative_caption": ["There are exactly 5 words total on the sign."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2353138", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381614.jpg", "positive_caption": ["There are exactly 4 kinds of vegetables shown."], "negative_caption": ["There are exactly 5 kinds of vegetables shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381614", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401086.jpg", "positive_caption": ["There are exactly 4 giraffes at least partially visible."], "negative_caption": ["There are exactly 3 giraffes at least partially visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401086", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340049.jpg", "positive_caption": ["There are exactly 6 pigeons."], "negative_caption": ["There are exactly 5 pigeons."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2340049", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397031.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2397031", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406729.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2406729", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315985.jpg", "positive_caption": ["There are exactly 8 vehicles on the street."], "negative_caption": ["There are exactly 5 vehicles on the street."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2315985", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360977.jpg", "positive_caption": ["There are exactly 2 trees in the foreground."], "negative_caption": ["There are exactly 5 trees in the foreground."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360977", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372611.jpg", "positive_caption": ["There are exactly 2 teams playing."], "negative_caption": ["There is exactly 1 team playing."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372611", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592677.jpg", "positive_caption": ["There are exactly 5 pizzas on the cookie sheet."], "negative_caption": ["There are exactly 3 pizzas on the cookie sheet."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592677", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387338.jpg", "positive_caption": ["There are exactly 5 people pictured."], "negative_caption": ["There is exactly 1 person pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2387338", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285772.jpg", "positive_caption": ["There are exactly 4 giraffes."], "negative_caption": ["There is exactly 1 giraffe."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_285772", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367736.jpg", "positive_caption": ["1 apple can we clearly see in this photo."], "negative_caption": ["0 apples can we clearly see in this photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367736", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362845.jpg", "positive_caption": ["There are exactly 2 horses."], "negative_caption": ["There are exactly 4 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362845", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373987.jpg", "positive_caption": ["There are exactly 8 legs."], "negative_caption": ["There are exactly 2 legs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373987", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371597.jpg", "positive_caption": ["There are exactly 0 cars."], "negative_caption": ["There are exactly 2 cars."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371597", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360457.jpg", "positive_caption": ["There are exactly 4 kites in the sky."], "negative_caption": ["There are exactly 5 kites in the sky."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360457", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390919.jpg", "positive_caption": ["There are exactly 6 olives on the pizza."], "negative_caption": ["There are exactly 8 olives on the pizza."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2390919", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397532.jpg", "positive_caption": ["There are exactly 7 cabinet doors on the top row."], "negative_caption": ["There are exactly 6 cabinet doors on the top row."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2397532", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369481.jpg", "positive_caption": ["There are exactly 3 chairs."], "negative_caption": ["There are exactly 2 chairs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369481", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362825.jpg", "positive_caption": ["There is exactly 1 woman."], "negative_caption": ["There are exactly 9 women."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362825", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375160.jpg", "positive_caption": ["There are exactly 4 buildings."], "negative_caption": ["There are exactly 2 buildings."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375160", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339555.jpg", "positive_caption": ["There are exactly 2 animals in the pic."], "negative_caption": ["There are exactly 9 animals in the pic."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2339555", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409813.jpg", "positive_caption": ["There are exactly 4 round glass containers."], "negative_caption": ["There are exactly 0 round glass containers."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2409813", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346768.jpg", "positive_caption": ["There are exactly 5 signs."], "negative_caption": ["There are exactly 7 signs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2346768", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713003.jpg", "positive_caption": ["There are exactly 4 men in the pictures."], "negative_caption": ["There are exactly 5 men in the pictures."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_713003", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406505.jpg", "positive_caption": ["There are exactly 6 people in the water."], "negative_caption": ["There are exactly 2 people in the water."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2406505", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362527.jpg", "positive_caption": ["There are exactly 2 trains shown."], "negative_caption": ["There are exactly 4 trains shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362527", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373851.jpg", "positive_caption": ["There are exactly 3 giraffes."], "negative_caption": ["There is exactly 1 giraffe."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373851", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367700.jpg", "positive_caption": ["There is exactly 1 flower pot."], "negative_caption": ["There are exactly 4 flower pots."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367700", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373345.jpg", "positive_caption": ["There are exactly 3 trees shown."], "negative_caption": ["There are exactly 10 trees shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373345", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385592.jpg", "positive_caption": ["There are exactly 12 people in the photo on motorbikes."], "negative_caption": ["There are exactly 0 people in the photo on motorbikes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2385592", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404185.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2404185", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363425.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363425", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325735.jpg", "positive_caption": ["There are exactly 6 buildings visible."], "negative_caption": ["There are exactly 8 buildings visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2325735", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398292.jpg", "positive_caption": ["There are exactly 5 sheep in the pasture."], "negative_caption": ["There are exactly 2 sheep in the pasture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2398292", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382438.jpg", "positive_caption": ["There are exactly 7 children."], "negative_caption": ["There are exactly 5 children."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2382438", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592568.jpg", "positive_caption": ["There are exactly 0 clouds."], "negative_caption": ["There is exactly 1 cloud."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592568", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332401.jpg", "positive_caption": ["There are exactly 7 garlic."], "negative_caption": ["There are exactly 3 garlic."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2332401", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385099.jpg", "positive_caption": ["There are exactly 4 trees in this image."], "negative_caption": ["There are exactly 6 trees in this image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2385099", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411479.jpg", "positive_caption": ["There are exactly 4 doughnuts appear to be yellow."], "negative_caption": ["There are exactly 12 doughnuts appear to be yellow."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2411479", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372290.jpg", "positive_caption": ["There are exactly 2 parking meters shown."], "negative_caption": ["There are exactly 3 parking meters shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372290", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367923.jpg", "positive_caption": ["There are exactly 2 banana stalks."], "negative_caption": ["There are exactly 4 banana stalks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367923", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413980.jpg", "positive_caption": ["There are exactly 5 women in the picture."], "negative_caption": ["There are exactly 4 women in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2413980", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362253.jpg", "positive_caption": ["There is exactly 1 plane."], "negative_caption": ["There are exactly 2 planes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362253", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404566.jpg", "positive_caption": ["There are exactly 5 kids in this photo."], "negative_caption": ["There are exactly 0 kids in this photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2404566", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372004.jpg", "positive_caption": ["There is exactly 1 bath tub."], "negative_caption": ["There are exactly 3 bath tubs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372004", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403382.jpg", "positive_caption": ["There are exactly 14 carrots."], "negative_caption": ["There are exactly 3 carrots."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403382", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392973.jpg", "positive_caption": ["There are exactly 0 people seen."], "negative_caption": ["There are exactly 10 people seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2392973", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713666.jpg", "positive_caption": ["There are exactly 0 people on the bus."], "negative_caption": ["There are exactly 4 people on the bus."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_713666", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_712985.jpg", "positive_caption": ["There are exactly 5 vehicles on the road."], "negative_caption": ["There are exactly 3 vehicles on the road."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_712985", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1160241.jpg", "positive_caption": ["There are exactly 10 cars parked behind the boats."], "negative_caption": ["There are exactly 4 cars parked behind the boats."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1160241", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360897.jpg", "positive_caption": ["There are exactly 2 sinks."], "negative_caption": ["There are exactly 11 sinks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360897", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367366.jpg", "positive_caption": ["There are exactly 2 people shown."], "negative_caption": ["There are exactly 3 people shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367366", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359425.jpg", "positive_caption": ["There are exactly 0 people pictured."], "negative_caption": ["There is exactly 1 person pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359425", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362476.jpg", "positive_caption": ["There are exactly 4 eagles visible."], "negative_caption": ["There are exactly 6 eagles visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362476", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371111.jpg", "positive_caption": ["There are exactly 0 animals in this picture."], "negative_caption": ["There are exactly 3 animals in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371111", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592538.jpg", "positive_caption": ["There are exactly 3 trees on the building."], "negative_caption": ["There are exactly 6 trees on the building."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592538", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367397.jpg", "positive_caption": ["There are exactly 2 lamps in the room."], "negative_caption": ["There are exactly 3 lamps in the room."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367397", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368059.jpg", "positive_caption": ["There are exactly 2 players in the picture."], "negative_caption": ["There are exactly 0 players in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368059", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354541.jpg", "positive_caption": ["There are exactly 6 potatoes on the counter."], "negative_caption": ["There are exactly 3 potatoes on the counter."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2354541", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368860.jpg", "positive_caption": ["There are exactly 6 players on the field."], "negative_caption": ["There are exactly 5 players on the field."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368860", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366274.jpg", "positive_caption": ["There is exactly 1 cat."], "negative_caption": ["There are exactly 6 cats."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366274", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361120.jpg", "positive_caption": ["There is exactly 1 dishe."], "negative_caption": ["There are exactly 2 dishes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361120", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387441.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2387441", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592315.jpg", "positive_caption": ["There are exactly 4 bananas hangng."], "negative_caption": ["There are exactly 2 bananas hangng."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592315", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374559.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374559", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375799.jpg", "positive_caption": ["There are exactly 2 planes."], "negative_caption": ["There is exactly 1 plane."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375799", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371491.jpg", "positive_caption": ["There is exactly 1 person in the picture."], "negative_caption": ["There are exactly 4 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371491", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373456.jpg", "positive_caption": ["There are exactly 9 muffins pictured."], "negative_caption": ["There are exactly 7 muffins pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373456", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370565.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 8 giraffes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370565", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380782.jpg", "positive_caption": ["There are exactly 4 horses."], "negative_caption": ["There are exactly 5 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2380782", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335679.jpg", "positive_caption": ["There are exactly 22 windows."], "negative_caption": ["There are exactly 5 windows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2335679", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369372.jpg", "positive_caption": ["There are exactly 12 kids."], "negative_caption": ["There are exactly 8 kids."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369372", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373481.jpg", "positive_caption": ["There are exactly 4 containers show food."], "negative_caption": ["There are exactly 7 containers show food."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373481", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326730.jpg", "positive_caption": ["There are exactly 5 people shown."], "negative_caption": ["There are exactly 0 people shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2326730", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380707.jpg", "positive_caption": ["There are exactly 13 blue cushions on the floor."], "negative_caption": ["There are exactly 8 blue cushions on the floor."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2380707", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591847.jpg", "positive_caption": ["There are exactly 3 cars parked."], "negative_caption": ["There are exactly 11 cars parked."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591847", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360542.jpg", "positive_caption": ["There are exactly 3 zippers on the bag."], "negative_caption": ["There is exactly 1 zipper on the bag."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360542", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394557.jpg", "positive_caption": ["There are exactly 0 people in this photo."], "negative_caption": ["There are exactly 2 people in this photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2394557", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360803.jpg", "positive_caption": ["There is exactly 1 car."], "negative_caption": ["There are exactly 2 cars."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360803", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386811.jpg", "positive_caption": ["There are exactly 4 jets."], "negative_caption": ["There are exactly 5 jets."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2386811", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349020.jpg", "positive_caption": ["There are exactly 5 people shown."], "negative_caption": ["There are exactly 0 people shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2349020", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1160031.jpg", "positive_caption": ["There are exactly 2 people at the curb."], "negative_caption": ["There are exactly 0 people at the curb."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1160031", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365151.jpg", "positive_caption": ["There are exactly 3 tiers on the serving piece."], "negative_caption": ["There are exactly 5 tiers on the serving piece."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365151", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373172.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 4 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373172", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343079.jpg", "positive_caption": ["There are exactly 6 animals pictured."], "negative_caption": ["There are exactly 4 animals pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2343079", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407241.jpg", "positive_caption": ["There are exactly 0 drivers at the wheel of the truck."], "negative_caption": ["There are exactly 3 drivers at the wheel of the truck."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2407241", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363491.jpg", "positive_caption": ["There are exactly 2 animals."], "negative_caption": ["There are exactly 0 animals."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363491", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406547.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2406547", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401904.jpg", "positive_caption": ["There are exactly 4 lanes of traffic on the right side of the median."], "negative_caption": ["There are exactly 5 lanes of traffic on the right side of the median."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401904", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398382.jpg", "positive_caption": ["There are exactly 4 zebras."], "negative_caption": ["There are exactly 5 zebras."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2398382", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375837.jpg", "positive_caption": ["There are exactly 4 writing utensils clearly visible."], "negative_caption": ["There are exactly 0 writing utensils clearly visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375837", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369637.jpg", "positive_caption": ["2 directions can cars travel on the road."], "negative_caption": ["5 directions can cars travel on the road."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369637", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330987.jpg", "positive_caption": ["There are exactly 20 scooters shown."], "negative_caption": ["There are exactly 2 scooters shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2330987", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362181.jpg", "positive_caption": ["There is exactly 1 pan."], "negative_caption": ["There are exactly 6 pans."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362181", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414484.jpg", "positive_caption": ["There are exactly 10 animals."], "negative_caption": ["There are exactly 2 animals."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2414484", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159638.jpg", "positive_caption": ["There are exactly 3 red double decker buses."], "negative_caption": ["There are exactly 0 red double decker buses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1159638", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364680.jpg", "positive_caption": ["There are exactly 3 chairs shown."], "negative_caption": ["There are exactly 7 chairs shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364680", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367131.jpg", "positive_caption": ["There are exactly 12 donuts in a box."], "negative_caption": ["There are exactly 6 donuts in a box."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367131", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417023.jpg", "positive_caption": ["There are exactly 7 raspberries pictured."], "negative_caption": ["There are exactly 5 raspberries pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2417023", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411251.jpg", "positive_caption": ["There are exactly 8 sinks."], "negative_caption": ["There are exactly 6 sinks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2411251", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405741.jpg", "positive_caption": ["5 players can be seen."], "negative_caption": ["10 players can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2405741", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363404.jpg", "positive_caption": ["There are exactly 2 plates."], "negative_caption": ["There are exactly 5 plates."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363404", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150522.jpg", "positive_caption": ["There are exactly 6 pillars on the dock."], "negative_caption": ["There are exactly 10 pillars on the dock."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_150522", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403284.jpg", "positive_caption": ["There are exactly 0 people pictured."], "negative_caption": ["There are exactly 3 people pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403284", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382769.jpg", "positive_caption": ["There are exactly 6 lights on the front of the train."], "negative_caption": ["There are exactly 8 lights on the front of the train."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2382769", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364009.jpg", "positive_caption": ["There are exactly 7 women in the photo."], "negative_caption": ["There are exactly 4 women in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364009", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341856.jpg", "positive_caption": ["There are exactly 5 sheep."], "negative_caption": ["There are exactly 2 sheep."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2341856", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367480.jpg", "positive_caption": ["There are exactly 6 crosses."], "negative_caption": ["There are exactly 3 crosses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367480", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367883.jpg", "positive_caption": ["There is exactly 1 bike."], "negative_caption": ["There are exactly 6 bikes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367883", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382251.jpg", "positive_caption": ["There are exactly 3 jars."], "negative_caption": ["There are exactly 0 jars."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2382251", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370415.jpg", "positive_caption": ["There is exactly 1 dog in the water."], "negative_caption": ["There are exactly 5 dogs in the water."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370415", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391324.jpg", "positive_caption": ["There are exactly 16 umbrellas."], "negative_caption": ["There are exactly 3 umbrellas."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2391324", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360776.jpg", "positive_caption": ["There are exactly 3 people."], "negative_caption": ["There are exactly 11 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360776", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362233.jpg", "positive_caption": ["There are exactly 3 zebras."], "negative_caption": ["There are exactly 2 zebras."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362233", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364676.jpg", "positive_caption": ["There are exactly 5 tires visible on the closest truck."], "negative_caption": ["There are exactly 3 tires visible on the closest truck."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364676", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361649.jpg", "positive_caption": ["There are exactly 5 birds."], "negative_caption": ["There are exactly 0 birds."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361649", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372519.jpg", "positive_caption": ["There are exactly 2 black noses."], "negative_caption": ["There is exactly 1 black nose."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372519", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713731.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_713731", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373066.jpg", "positive_caption": ["There are exactly 2 get awards."], "negative_caption": ["There is exactly 1 get award."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373066", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402788.jpg", "positive_caption": ["There are exactly 0 people in picture."], "negative_caption": ["There is exactly 1 person in picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2402788", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386509.jpg", "positive_caption": ["There are exactly 0 animals in this picture."], "negative_caption": ["There is exactly 1 animal in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2386509", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364534.jpg", "positive_caption": ["There are exactly 2 devices on."], "negative_caption": ["There is exactly 1 device on."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364534", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285923.jpg", "positive_caption": ["There are exactly 0 trains on the tracks."], "negative_caption": ["There is exactly 1 train on the tracks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_285923", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366368.jpg", "positive_caption": ["There are exactly 12 small cups shown."], "negative_caption": ["There are exactly 5 small cups shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366368", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340891.jpg", "positive_caption": ["There are exactly 14 people pictured."], "negative_caption": ["There are exactly 3 people pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2340891", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372701.jpg", "positive_caption": ["There are exactly 2 legs visible."], "negative_caption": ["There are exactly 6 legs visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372701", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374056.jpg", "positive_caption": ["There is exactly 1 tenni racket."], "negative_caption": ["There are exactly 0 tennis rackets."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374056", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390402.jpg", "positive_caption": ["0 pieces have been taken from the pizza."], "negative_caption": ["1 pieces have been taken from the pizza."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2390402", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341467.jpg", "positive_caption": ["There are exactly 5 colors on the plane."], "negative_caption": ["There are exactly 2 colors on the plane."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2341467", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410671.jpg", "positive_caption": ["There are exactly 4 giraffes."], "negative_caption": ["There are exactly 6 giraffes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2410671", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342667.jpg", "positive_caption": ["There are exactly 5 birds."], "negative_caption": ["There are exactly 3 birds."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2342667", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370834.jpg", "positive_caption": ["There are exactly 9 people in the picture."], "negative_caption": ["There are exactly 5 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370834", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369658.jpg", "positive_caption": ["There are exactly 8 toys on the bed."], "negative_caption": ["There are exactly 3 toys on the bed."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369658", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403589.jpg", "positive_caption": ["There are exactly 6 candles on the cake."], "negative_caption": ["There is exactly 1 candle on the cake."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403589", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396705.jpg", "positive_caption": ["There are exactly 4 colors on the kite."], "negative_caption": ["There are exactly 3 colors on the kite."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2396705", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401779.jpg", "positive_caption": ["There are exactly 4 bears."], "negative_caption": ["There is exactly 1 bear."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401779", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412494.jpg", "positive_caption": ["There are exactly 5 lights on the traffic light."], "negative_caption": ["There are exactly 6 lights on the traffic light."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2412494", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363884.jpg", "positive_caption": ["There are exactly 11 carrots."], "negative_caption": ["There are exactly 5 carrots."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363884", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367879.jpg", "positive_caption": ["There are exactly 3 stuffed animals."], "negative_caption": ["There are exactly 4 stuffed animals."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367879", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376568.jpg", "positive_caption": ["There are exactly 3 people in the photo."], "negative_caption": ["There are exactly 5 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2376568", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384064.jpg", "positive_caption": ["There are exactly 5 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2384064", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370551.jpg", "positive_caption": ["There is exactly 1 horse."], "negative_caption": ["There are exactly 4 horse."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370551", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360672.jpg", "positive_caption": ["There are exactly 2 eyes on the elephant."], "negative_caption": ["There are exactly 3 eyes on the elephant."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360672", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371019.jpg", "positive_caption": ["There are exactly 3 women."], "negative_caption": ["There are exactly 6 women."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371019", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370656.jpg", "positive_caption": ["There are exactly 2 giraffes shown."], "negative_caption": ["There are exactly 3 giraffes shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370656", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381918.jpg", "positive_caption": ["There are exactly 3 people shown."], "negative_caption": ["There are exactly 5 people shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2381918", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322813.jpg", "positive_caption": ["There are exactly 6 horses."], "negative_caption": ["There are exactly 5 horses."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2322813", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400921.jpg", "positive_caption": ["There are exactly 0 dinosaurs in the picture."], "negative_caption": ["There is exactly 1 dinosaur in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2400921", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359288.jpg", "positive_caption": ["There are exactly 5 people shown in total."], "negative_caption": ["There are exactly 0 people shown in total."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359288", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393859.jpg", "positive_caption": ["There are exactly 0 people in the room."], "negative_caption": ["There is exactly 1 person in the room."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2393859", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315398.jpg", "positive_caption": ["There are exactly 9 donuts in the box."], "negative_caption": ["There are exactly 4 donuts in the box."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2315398", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398412.jpg", "positive_caption": ["There are exactly 0 people pictured."], "negative_caption": ["There is exactly 1 person pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2398412", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363629.jpg", "positive_caption": ["There are exactly 2 bears in the picture."], "negative_caption": ["There are exactly 5 bears in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363629", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366778.jpg", "positive_caption": ["There are exactly 3 women in the picture."], "negative_caption": ["There are exactly 7 women in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366778", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410209.jpg", "positive_caption": ["There are exactly 5 animals visible."], "negative_caption": ["There are exactly 0 animals visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2410209", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401498.jpg", "positive_caption": ["There are exactly 4 knobs on the stove."], "negative_caption": ["There are exactly 5 knobs on the stove."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2401498", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368127.jpg", "positive_caption": ["There is exactly 1 horse in the picture."], "negative_caption": ["There are exactly 3 horses in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368127", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409603.jpg", "positive_caption": ["There are exactly 0 dogs on the beach."], "negative_caption": ["There are exactly 2 dogs on the beach."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2409603", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364407.jpg", "positive_caption": ["There are exactly 3 teachers."], "negative_caption": ["There are exactly 4 teachers."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364407", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327843.jpg", "positive_caption": ["There are exactly 5 bus stops."], "negative_caption": ["There are exactly 0 bus stops."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2327843", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410005.jpg", "positive_caption": ["There are exactly 0 spectators in the first four rows."], "negative_caption": ["There are exactly 30 spectators in the first four rows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2410005", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374101.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 4 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374101", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374787.jpg", "positive_caption": ["There are exactly 5 umbrellas shown."], "negative_caption": ["There are exactly 6 umbrellas shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374787", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391415.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2391415", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_286095.jpg", "positive_caption": ["There are exactly 3 buildings surround the clock tower."], "negative_caption": ["There are exactly 4 buildings surround the clock tower."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_286095", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363637.jpg", "positive_caption": ["There is exactly 1 tenni player."], "negative_caption": ["There are exactly 2 tennis players."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363637", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362983.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There are exactly 14 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362983", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364013.jpg", "positive_caption": ["There are exactly 3 people on the field."], "negative_caption": ["There are exactly 5 people on the field."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364013", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159405.jpg", "positive_caption": ["There is exactly 1 train on the tracks."], "negative_caption": ["There are exactly 2 trains on the tracks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1159405", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374900.jpg", "positive_caption": ["10 flags can be seen."], "negative_caption": ["12 flags can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374900", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367527.jpg", "positive_caption": ["There is exactly 1 cake."], "negative_caption": ["There are exactly 0 cakes."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367527", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364864.jpg", "positive_caption": ["There is exactly 1 ball."], "negative_caption": ["There are exactly 3 balls."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364864", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368500.jpg", "positive_caption": ["There are exactly 10 people in the image."], "negative_caption": ["There are exactly 4 people in the image."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368500", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360220.jpg", "positive_caption": ["There are exactly 3 toothbrush covers."], "negative_caption": ["There are exactly 0 toothbrush covers."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360220", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365133.jpg", "positive_caption": ["There are exactly 5 people in the photo."], "negative_caption": ["There are exactly 4 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365133", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373711.jpg", "positive_caption": ["There are exactly 3 people in the background of the photo."], "negative_caption": ["There are exactly 5 people in the background of the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373711", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370171.jpg", "positive_caption": ["There is exactly 1 elephant."], "negative_caption": ["There are exactly 8 elephant."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370171", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369228.jpg", "positive_caption": ["There are exactly 2 people in the photo."], "negative_caption": ["There are exactly 6 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369228", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415803.jpg", "positive_caption": ["There are exactly 4 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2415803", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361996.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 5 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361996", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373822.jpg", "positive_caption": ["There are exactly 3 trains."], "negative_caption": ["There are exactly 4 trains."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2373822", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344799.jpg", "positive_caption": ["There are exactly 11 bananas being held."], "negative_caption": ["There are exactly 8 bananas being held."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2344799", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592724.jpg", "positive_caption": ["There are exactly 4 chairs."], "negative_caption": ["There are exactly 10 chairs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592724", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398411.jpg", "positive_caption": ["There are exactly 4 elephants."], "negative_caption": ["There are exactly 5 elephants."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2398411", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360364.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 4 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360364", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360734.jpg", "positive_caption": ["There are exactly 4 people in the picture."], "negative_caption": ["There are exactly 6 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360734", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372230.jpg", "positive_caption": ["There are exactly 0 people visible."], "negative_caption": ["There are exactly 5 people visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372230", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361728.jpg", "positive_caption": ["There is exactly 1 surfer."], "negative_caption": ["There are exactly 3 surfers."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2361728", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366968.jpg", "positive_caption": ["There are exactly 2 vehicles shown."], "negative_caption": ["There are exactly 6 vehicles shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366968", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403164.jpg", "positive_caption": ["There are exactly 12 roman numerals on the clock."], "negative_caption": ["There are exactly 9 roman numerals on the clock."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2403164", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592135.jpg", "positive_caption": ["There are exactly 5 boats on the beach."], "negative_caption": ["There is exactly 1 boat on the beach."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1592135", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377779.jpg", "positive_caption": ["There are exactly 4 pieces."], "negative_caption": ["There are exactly 9 pieces."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377779", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394783.jpg", "positive_caption": ["There are exactly 0 people in the kitchen."], "negative_caption": ["There are exactly 4 people in the kitchen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2394783", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364876.jpg", "positive_caption": ["There are exactly 2 mirrors."], "negative_caption": ["There is exactly 1 mirror."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2364876", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386897.jpg", "positive_caption": ["There are exactly 5 crosses on the building."], "negative_caption": ["There are exactly 0 crosses on the building."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2386897", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367560.jpg", "positive_caption": ["There are exactly 2 cooks."], "negative_caption": ["There are exactly 5 cooks."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367560", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385765.jpg", "positive_caption": ["There are exactly 8 stairs visible."], "negative_caption": ["There are exactly 6 stairs visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2385765", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407788.jpg", "positive_caption": ["There are exactly 8 slices of pizza."], "negative_caption": ["There are exactly 7 slices of pizza."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2407788", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320102.jpg", "positive_caption": ["There are exactly 5 dogs."], "negative_caption": ["There are exactly 2 dogs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2320102", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375511.jpg", "positive_caption": ["There are exactly 2 red signs."], "negative_caption": ["There are exactly 4 red signs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2375511", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371756.jpg", "positive_caption": ["There are exactly 2 adults shown."], "negative_caption": ["There are exactly 6 adults shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371756", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374894.jpg", "positive_caption": ["There are exactly 2 zebra in the picture."], "negative_caption": ["There are exactly 8 zebra in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374894", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370512.jpg", "positive_caption": ["There are exactly 5 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370512", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345853.jpg", "positive_caption": ["There are exactly 6 umbrellas in this picture."], "negative_caption": ["There are exactly 5 umbrellas in this picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2345853", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367875.jpg", "positive_caption": ["There are exactly 3 wheels pictured."], "negative_caption": ["There are exactly 5 wheels pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367875", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352855.jpg", "positive_caption": ["There are exactly 5 carts."], "negative_caption": ["There are exactly 6 carts."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2352855", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321028.jpg", "positive_caption": ["There are exactly 12 numbers on the clock."], "negative_caption": ["There are exactly 10 numbers on the clock."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2321028", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387563.jpg", "positive_caption": ["There are exactly 5 cars."], "negative_caption": ["There are exactly 2 cars."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2387563", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362752.jpg", "positive_caption": ["There are exactly 5 skateboarders."], "negative_caption": ["There are exactly 6 skateboarders."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2362752", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371493.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371493", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372530.jpg", "positive_caption": ["There is exactly 1 bird."], "negative_caption": ["There are exactly 0 birds."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2372530", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369707.jpg", "positive_caption": ["There are exactly 2 laptops."], "negative_caption": ["There are exactly 3 laptops."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369707", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338537.jpg", "positive_caption": ["13 vases can be seen."], "negative_caption": ["0 vases can be seen."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2338537", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394614.jpg", "positive_caption": ["There are exactly 6 cabinet doors shown at the top of the photo."], "negative_caption": ["There are exactly 3 cabinet doors shown at the top of the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2394614", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416322.jpg", "positive_caption": ["There are exactly 4 people in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2416322", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376215.jpg", "positive_caption": ["There are exactly 3 wheels on the bottom of the plane."], "negative_caption": ["There are exactly 0 wheels on the bottom of the plane."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2376215", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350104.jpg", "positive_caption": ["There are exactly 7 people."], "negative_caption": ["There are exactly 6 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2350104", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329503.jpg", "positive_caption": ["There are exactly 12 letters and numbers on the street sign."], "negative_caption": ["There are exactly 2 letters and numbers on the street sign."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2329503", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358800.jpg", "positive_caption": ["There are exactly 5 people shown."], "negative_caption": ["There are exactly 4 people shown."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2358800", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368475.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 4 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2368475", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366833.jpg", "positive_caption": ["There are exactly 3 they."], "negative_caption": ["There are exactly 5 they."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2366833", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374366.jpg", "positive_caption": ["There are exactly 6 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2374366", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316697.jpg", "positive_caption": ["There are exactly 6 planes flying."], "negative_caption": ["There are exactly 5 planes flying."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2316697", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409749.jpg", "positive_caption": ["There are exactly 5 giraffes in the picture."], "negative_caption": ["There are exactly 0 giraffes in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2409749", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398494.jpg", "positive_caption": ["There are exactly 10 knives in the picture."], "negative_caption": ["There are exactly 5 knives in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2398494", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371600.jpg", "positive_caption": ["There are exactly 5 women."], "negative_caption": ["There are exactly 4 women."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2371600", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411827.jpg", "positive_caption": ["There are exactly 0 people visible."], "negative_caption": ["There is exactly 1 person visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2411827", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591873.jpg", "positive_caption": ["There are exactly 3 drawers in the night stand."], "negative_caption": ["There is exactly 1 drawer in the night stand."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_1591873", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392566.jpg", "positive_caption": ["There are exactly 11 people in the picture."], "negative_caption": ["There are exactly 7 people in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2392566", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370194.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 4 giraffe."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370194", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369856.jpg", "positive_caption": ["There are exactly 3 zebras on the plain."], "negative_caption": ["There are exactly 5 zebras on the plain."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2369856", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363785.jpg", "positive_caption": ["There are exactly 5 french fries."], "negative_caption": ["There are exactly 0 french fries."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363785", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356252.jpg", "positive_caption": ["There are exactly 8 legs."], "negative_caption": ["There are exactly 0 legs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2356252", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363747.jpg", "positive_caption": ["There is exactly 1 racket in the photo."], "negative_caption": ["There are exactly 4 rackets in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2363747", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365252.jpg", "positive_caption": ["There is exactly 1 truck pictured."], "negative_caption": ["There are exactly 0 trucks pictured."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2365252", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389969.jpg", "positive_caption": ["There are exactly 5 wax figures in the picture."], "negative_caption": ["There are exactly 3 wax figures in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2389969", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376178.jpg", "positive_caption": ["There are exactly 3 bananas in the picture."], "negative_caption": ["There are exactly 4 bananas in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2376178", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713025.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_713025", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360158.jpg", "positive_caption": ["There are exactly 2 arrows."], "negative_caption": ["There are exactly 5 arrows."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2360158", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376829.jpg", "positive_caption": ["There are exactly 3 sets of train tracks in the photo."], "negative_caption": ["There are exactly 5 sets of train tracks in the photo."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2376829", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389881.jpg", "positive_caption": ["There are exactly 4 windows visible."], "negative_caption": ["There are exactly 6 windows visible."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2389881", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359914.jpg", "positive_caption": ["There is exactly 1 bird flying."], "negative_caption": ["There are exactly 6 birds flying."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2359914", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411689.jpg", "positive_caption": ["There are exactly 5 structures in the picture."], "negative_caption": ["There are exactly 0 structures in the picture."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2411689", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377477.jpg", "positive_caption": ["There are exactly 6 chairs."], "negative_caption": ["There are exactly 9 chairs."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2377477", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345651.jpg", "positive_caption": ["There are exactly 11 thin rings appear on the vase."], "negative_caption": ["There are exactly 19 thin rings appear on the vase."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2345651", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367579.jpg", "positive_caption": ["There are exactly 3 bracelets on the guy."], "negative_caption": ["There are exactly 0 bracelets on the guy."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2367579", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370179.jpg", "positive_caption": ["There are exactly 2 trees."], "negative_caption": ["There are exactly 0 trees."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2370179", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388767.jpg", "positive_caption": ["There are exactly 0 clouds in the sky."], "negative_caption": ["There is exactly 1 cloud in the sky."], "original_file_name": "counting-hard", "dataset": "visual7w", "key": "counting_visual7w_2388767", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349294.jpg", "positive_caption": ["Cars are allowed to park for exactly 2 hours from 8 am to 6 pm."], "negative_caption": ["Cars are allowed to park for exactly 1 hour from 8 am to 6 pm."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2349294", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344761.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2344761", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362253.jpg", "positive_caption": ["There is exactly 1 plane."], "negative_caption": ["There are exactly 2 planes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362253", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394354.jpg", "positive_caption": ["There are exactly 2 birds."], "negative_caption": ["There are exactly 3 birds."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2394354", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324167.jpg", "positive_caption": ["There are exactly 3 colors on the floor."], "negative_caption": ["There are exactly 0 colors on the floor."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2324167", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321230.jpg", "positive_caption": ["There are exactly 2 trains pictured."], "negative_caption": ["There is exactly 1 train pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2321230", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339987.jpg", "positive_caption": ["There are exactly 0 animals in this picture."], "negative_caption": ["There are exactly 3 animals in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339987", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369481.jpg", "positive_caption": ["There are exactly 3 chairs."], "negative_caption": ["There are exactly 2 chairs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2369481", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713258.jpg", "positive_caption": ["There is exactly 1 elephant."], "negative_caption": ["There are exactly 2 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713258", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591944.jpg", "positive_caption": ["There are exactly 3 wheels."], "negative_caption": ["There are exactly 2 wheels."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1591944", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362452.jpg", "positive_caption": ["There is exactly 1 foot on the skateboard."], "negative_caption": ["There are exactly 2 feet on the skateboard."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362452", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367366.jpg", "positive_caption": ["There are exactly 2 people shown."], "negative_caption": ["There is exactly 1 person shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367366", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381467.jpg", "positive_caption": ["There is exactly 1 train shown."], "negative_caption": ["There are exactly 2 trains shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381467", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391135.jpg", "positive_caption": ["There are exactly 3 people in the picture."], "negative_caption": ["There are exactly 0 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2391135", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317623.jpg", "positive_caption": ["There is exactly 1 hot dog."], "negative_caption": ["There are exactly 2 hot dogs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2317623", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390942.jpg", "positive_caption": ["You see exactly 0 people."], "negative_caption": ["You see exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2390942", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319888.jpg", "positive_caption": ["There are exactly 2 bicycles in the picture."], "negative_caption": ["There are exactly 3 bicycles in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2319888", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395218.jpg", "positive_caption": ["There is exactly 1 bird on the railing."], "negative_caption": ["There are exactly 2 birds on the railing."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2395218", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_286095.jpg", "positive_caption": ["There are exactly 3 buildings surround the clock tower."], "negative_caption": ["There is exactly 1 building surround the clock tower."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_286095", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408682.jpg", "positive_caption": ["There are exactly 3 elephants in the picture."], "negative_caption": ["There are exactly 2 elephants in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2408682", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592615.jpg", "positive_caption": ["There are exactly 2 computers."], "negative_caption": ["There are exactly 3 computers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592615", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413440.jpg", "positive_caption": ["There is exactly 1 elephant."], "negative_caption": ["There are exactly 2 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413440", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392825.jpg", "positive_caption": ["There are exactly 3 giraffes shown."], "negative_caption": ["There is exactly 1 giraffe shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2392825", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398772.jpg", "positive_caption": ["There is exactly 1 tree in the image."], "negative_caption": ["There are exactly 2 trees in the image."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398772", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150543.jpg", "positive_caption": ["There are exactly 3 windows shown."], "negative_caption": ["There are exactly 0 windows shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_150543", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394412.jpg", "positive_caption": ["There is exactly 1 kid batting."], "negative_caption": ["There are exactly 2 kids batting."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2394412", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592899.jpg", "positive_caption": ["There are exactly 2 buildings the flags hung from."], "negative_caption": ["There is exactly 1 building the flags hung from."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592899", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348579.jpg", "positive_caption": ["There are exactly 2 hot dogs."], "negative_caption": ["There are exactly 3 hot dogs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348579", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401311.jpg", "positive_caption": ["There are exactly 3 lights."], "negative_caption": ["There are exactly 2 lights."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401311", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382406.jpg", "positive_caption": ["There are exactly 2 candles."], "negative_caption": ["There are exactly 3 candles."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2382406", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397504.jpg", "positive_caption": ["There are exactly 3 paper bag."], "negative_caption": ["There is exactly 1 paper bag."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397504", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327763.jpg", "positive_caption": ["There are exactly 0 people visible."], "negative_caption": ["There is exactly 1 person visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327763", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382102.jpg", "positive_caption": ["There is exactly 1 boat."], "negative_caption": ["There are exactly 2 boats."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2382102", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326658.jpg", "positive_caption": ["There are exactly 3 people sitting on the bench."], "negative_caption": ["There are exactly 2 people sitting on the bench."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2326658", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416589.jpg", "positive_caption": ["There are exactly 2 cows."], "negative_caption": ["There is exactly 1 cow."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416589", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371901.jpg", "positive_caption": ["There is exactly 1 green object on the floor."], "negative_caption": ["There are exactly 2 green objects on the floor."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371901", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390632.jpg", "positive_caption": ["There are exactly 2 signs in the photo."], "negative_caption": ["There is exactly 1 sign in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2390632", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330406.jpg", "positive_caption": ["There is exactly 1 screen shown."], "negative_caption": ["There are exactly 2 screens shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2330406", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392714.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2392714", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358152.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2358152", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334774.jpg", "positive_caption": ["There is exactly 1 man on the field."], "negative_caption": ["There are exactly 2 men on the field."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334774", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150258.jpg", "positive_caption": ["There are exactly 0 buildings in the photo."], "negative_caption": ["There are exactly 2 buildings in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_150258", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398392.jpg", "positive_caption": ["There is exactly 1 woman in the room."], "negative_caption": ["There are exactly 2 women in the room."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398392", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373955.jpg", "positive_caption": ["There are exactly 2 dogs."], "negative_caption": ["There are exactly 3 dogs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2373955", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362181.jpg", "positive_caption": ["There is exactly 1 pan."], "negative_caption": ["There are exactly 3 pans."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362181", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321323.jpg", "positive_caption": ["There are exactly 3 red umbrellas."], "negative_caption": ["There is exactly 1 red umbrella."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2321323", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150356.jpg", "positive_caption": ["There are exactly 2 people wearing slippers."], "negative_caption": ["There are exactly 3 people wearing slippers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_150356", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320133.jpg", "positive_caption": ["There is exactly 1 vase."], "negative_caption": ["There are exactly 2 vases."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320133", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390850.jpg", "positive_caption": ["There are exactly 0 people in the water."], "negative_caption": ["There is exactly 1 person in the water."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2390850", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388378.jpg", "positive_caption": ["There are exactly 2 skiers."], "negative_caption": ["There is exactly 1 skier."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2388378", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356195.jpg", "positive_caption": ["There are exactly 3 chairs seen."], "negative_caption": ["There are exactly 0 chairs seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2356195", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357171.jpg", "positive_caption": ["There is exactly 1 tree."], "negative_caption": ["There are exactly 2 trees."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2357171", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400851.jpg", "positive_caption": ["There are exactly 2 elephants."], "negative_caption": ["There are exactly 3 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2400851", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320820.jpg", "positive_caption": ["There are exactly 2 glasses."], "negative_caption": ["There is exactly 1 glass."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320820", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319737.jpg", "positive_caption": ["There are exactly 2 cars."], "negative_caption": ["There are exactly 3 cars."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2319737", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417211.jpg", "positive_caption": ["There are exactly 3 boards."], "negative_caption": ["There are exactly 2 boards."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2417211", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341686.jpg", "positive_caption": ["There are exactly 0 people sitting on the couch."], "negative_caption": ["There are exactly 2 people sitting on the couch."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341686", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359931.jpg", "positive_caption": ["There are exactly 2 kids."], "negative_caption": ["There are exactly 3 kids."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359931", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318472.jpg", "positive_caption": ["There are exactly 3 chairs in front of the buildings."], "negative_caption": ["There are exactly 0 chairs in front of the buildings."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2318472", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356590.jpg", "positive_caption": ["Exactly 2 animals can be seen."], "negative_caption": ["Exactly 3 animals can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2356590", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416583.jpg", "positive_caption": ["There are exactly 3 automobiles visible."], "negative_caption": ["There are exactly 2 automobiles visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416583", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330224.jpg", "positive_caption": ["There are exactly 3 different pictures."], "negative_caption": ["There is exactly 1 different picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2330224", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366303.jpg", "positive_caption": ["There are exactly 3 total lamps."], "negative_caption": ["There is exactly 1 total lamp."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2366303", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344214.jpg", "positive_caption": ["There are exactly 3 lights on the signal light."], "negative_caption": ["There are exactly 0 lights on the signal light."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2344214", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350806.jpg", "positive_caption": ["There is exactly 1 little girl."], "negative_caption": ["There are exactly 2 little girls."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2350806", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372326.jpg", "positive_caption": ["There are exactly 3 slalom poles."], "negative_caption": ["There is exactly 1 slalom pole."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2372326", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401254.jpg", "positive_caption": ["There are exactly 3 colors in the skateboard."], "negative_caption": ["There are exactly 2 colors in the skateboard."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401254", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416322.jpg", "positive_caption": ["There are exactly 3 people wearing glasses."], "negative_caption": ["There are exactly 2 people wearing glasses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416322", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381480.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 2 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381480", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382635.jpg", "positive_caption": ["There are exactly 3 boats."], "negative_caption": ["There is exactly 1 boat."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2382635", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368862.jpg", "positive_caption": ["There is exactly 1 horse."], "negative_caption": ["There are exactly 0 horses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2368862", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371980.jpg", "positive_caption": ["There is exactly 1 kind of animals in the picture."], "negative_caption": ["There are exactly 0 kinds of animals in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371980", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409603.jpg", "positive_caption": ["There are exactly 0 dogs on the beach."], "negative_caption": ["There are exactly 3 dogs on the beach."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2409603", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316941.jpg", "positive_caption": ["There are exactly 3 TV controllers below the TV."], "negative_caption": ["There are exactly 0 TV controllers below the TV."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2316941", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343236.jpg", "positive_caption": ["There are exactly 0 people pictured."], "negative_caption": ["There are exactly 3 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2343236", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318597.jpg", "positive_caption": ["There are exactly 2 elephants."], "negative_caption": ["There are exactly 0 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2318597", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342524.jpg", "positive_caption": ["There is exactly 1 vase on the table."], "negative_caption": ["There are exactly 3 vases on the table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2342524", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368105.jpg", "positive_caption": ["There are exactly 3 boats on the side of the building."], "negative_caption": ["There are exactly 2 boats on the side of the building."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2368105", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407799.jpg", "positive_caption": ["There is exactly 1 animal in this picture."], "negative_caption": ["There are exactly 3 animals in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2407799", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321924.jpg", "positive_caption": ["There are exactly 2 burgers pictured."], "negative_caption": ["There are exactly 0 burgers pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2321924", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363189.jpg", "positive_caption": ["There is exactly 1 bench."], "negative_caption": ["There are exactly 3 benches."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2363189", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410457.jpg", "positive_caption": ["There are exactly 3 people under the umbrella."], "negative_caption": ["There are exactly 2 people under the umbrella."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2410457", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376097.jpg", "positive_caption": ["There is exactly 1 bird in each photo."], "negative_caption": ["There are exactly 3 birds in each photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2376097", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362233.jpg", "positive_caption": ["There are exactly 3 zebras."], "negative_caption": ["There are exactly 1 zebras."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362233", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359914.jpg", "positive_caption": ["There is exactly 1 bird flying."], "negative_caption": ["There are exactly 2 birds flying."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359914", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322408.jpg", "positive_caption": ["There are exactly 2 horses."], "negative_caption": ["There are exactly 3 horses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2322408", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339394.jpg", "positive_caption": ["There is exactly 1 full slices of pizza in the picture."], "negative_caption": ["There are exactly 3 full slices of pizza in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339394", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367780.jpg", "positive_caption": ["There is exactly 1 pizza."], "negative_caption": ["There are exactly 2 pizzas."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367780", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414881.jpg", "positive_caption": ["There are exactly 2 men holding the tiger."], "negative_caption": ["There are exactly 0 men holding the tiger."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2414881", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713896.jpg", "positive_caption": ["There are exactly 2 brown chairs."], "negative_caption": ["There are exactly 3 brown chairs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713896", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385711.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2385711", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367575.jpg", "positive_caption": ["There is exactly 1 man in the picture."], "negative_caption": ["There are exactly 0 men in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367575", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346733.jpg", "positive_caption": ["There are exactly 0 people in the shot."], "negative_caption": ["There is exactly 1 person in the shot."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2346733", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325025.jpg", "positive_caption": ["There are exactly 3 yaks."], "negative_caption": ["There is exactly 1 yak."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2325025", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327218.jpg", "positive_caption": ["There are exactly 3 people smiling."], "negative_caption": ["There are exactly 0 people smiling."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327218", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321661.jpg", "positive_caption": ["There are exactly 3 planters."], "negative_caption": ["There is exactly 1 planter."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2321661", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339560.jpg", "positive_caption": ["There are exactly 2 birds flying."], "negative_caption": ["There is exactly 1 bird flying."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339560", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327129.jpg", "positive_caption": ["There is exactly 1 truck in the picture."], "negative_caption": ["There are exactly 3 trucks in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327129", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370926.jpg", "positive_caption": ["There is exactly 1 player visible."], "negative_caption": ["There are exactly 2 players visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370926", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327425.jpg", "positive_caption": ["There are exactly 3 main people."], "negative_caption": ["There is exactly 1 main person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327425", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381773.jpg", "positive_caption": ["There is exactly 1 box in the image."], "negative_caption": ["There are exactly 2 boxes in the image."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381773", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337207.jpg", "positive_caption": ["There are exactly 3 hands total shown."], "negative_caption": ["There are exactly 2 hands total shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2337207", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401999.jpg", "positive_caption": ["There are exactly 2 pair of shoes."], "negative_caption": ["There is exactly 1 pair of shoes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401999", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387915.jpg", "positive_caption": ["There are exactly 2 people visible."], "negative_caption": ["There are exactly 3 people visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2387915", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592844.jpg", "positive_caption": ["There are exactly 0 towels."], "negative_caption": ["There is exactly 1 towel."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592844", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381236.jpg", "positive_caption": ["There are exactly 2 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381236", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378828.jpg", "positive_caption": ["There are exactly 2 boots on the bench."], "negative_caption": ["There are exactly 3 boots on the bench."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2378828", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373172.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2373172", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350078.jpg", "positive_caption": ["There are exactly 2 boys in the image."], "negative_caption": ["There is exactly 1 boy in the image."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2350078", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333173.jpg", "positive_caption": ["There is exactly 1 plate."], "negative_caption": ["There are exactly 2 plates."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2333173", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358523.jpg", "positive_caption": ["There are exactly 3 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2358523", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316919.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2316919", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592555.jpg", "positive_caption": ["There is exactly 1 dog."], "negative_caption": ["There are exactly 3 dogs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592555", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375211.jpg", "positive_caption": ["There are exactly 2 pizzas on the table."], "negative_caption": ["There is exactly 1 pizza on the table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2375211", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391867.jpg", "positive_caption": ["There are exactly 3 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2391867", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388437.jpg", "positive_caption": ["There are exactly 2 train tracks shown."], "negative_caption": ["There are exactly 3 train tracks shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2388437", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327728.jpg", "positive_caption": ["There are exactly 2 stools."], "negative_caption": ["There is exactly 1 stool."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327728", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401137.jpg", "positive_caption": ["There are exactly 3 dogs on the motorbike."], "negative_caption": ["There is exactly 1 dog on the motorbike."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401137", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323364.jpg", "positive_caption": ["There are exactly 0 cats."], "negative_caption": ["There is exactly 1 cat."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2323364", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389720.jpg", "positive_caption": ["There is exactly 1 person in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2389720", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369515.jpg", "positive_caption": ["There are exactly 3 capital letters pictured."], "negative_caption": ["There are exactly 2 capital letters pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2369515", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333318.jpg", "positive_caption": ["There are exactly 2 street signs."], "negative_caption": ["There is exactly 1 street sign."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2333318", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414603.jpg", "positive_caption": ["There is exactly 1 horse in the photo."], "negative_caption": ["There are exactly 3 horses in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2414603", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325633.jpg", "positive_caption": ["There are exactly 3 animals shown."], "negative_caption": ["There are exactly 2 animals shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2325633", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371080.jpg", "positive_caption": ["There is exactly 1 microwave."], "negative_caption": ["There are exactly 2 microwaves."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371080", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316787.jpg", "positive_caption": ["There are exactly 2 buildings in the picture."], "negative_caption": ["There are exactly 3 buildings in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2316787", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397743.jpg", "positive_caption": ["There are exactly 2 traffic lights."], "negative_caption": ["There are exactly 0 traffic lights."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397743", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331218.jpg", "positive_caption": ["There is exactly 1 kitten."], "negative_caption": ["There are exactly 2 kittens."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2331218", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405089.jpg", "positive_caption": ["There are exactly 2 donuts shown."], "negative_caption": ["There is exactly 1 donut shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2405089", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405530.jpg", "positive_caption": ["There is exactly 1 umbrella."], "negative_caption": ["There are exactly 2 umbrellas."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2405530", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400911.jpg", "positive_caption": ["There are exactly 3 tables."], "negative_caption": ["There are exactly 2 tables."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2400911", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367875.jpg", "positive_caption": ["There are exactly 3 wheels pictured."], "negative_caption": ["There are exactly 2 wheels pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367875", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329487.jpg", "positive_caption": ["There is exactly 1 dresser."], "negative_caption": ["There are exactly 3 dressers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2329487", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323223.jpg", "positive_caption": ["There is exactly 1 elephant."], "negative_caption": ["There are exactly 3 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2323223", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372612.jpg", "positive_caption": ["There are exactly 2 cars in the lower left of the photo."], "negative_caption": ["There are exactly 3 cars in the lower left of the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2372612", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402413.jpg", "positive_caption": ["There is exactly 1 animal in the photo."], "negative_caption": ["There are exactly 0 animals in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2402413", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320369.jpg", "positive_caption": ["There is exactly 1 train."], "negative_caption": ["There are exactly 2 trains."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320369", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365558.jpg", "positive_caption": ["There are exactly 3 traffic lights pictured."], "negative_caption": ["There are exactly 2 traffic lights pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2365558", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383458.jpg", "positive_caption": ["There are exactly 0 people in the image."], "negative_caption": ["There are exactly 3 people in the image."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2383458", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406060.jpg", "positive_caption": ["There is exactly 1 man."], "negative_caption": ["There are exactly 2 men."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2406060", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381618.jpg", "positive_caption": ["There is exactly 1 dog in the photo."], "negative_caption": ["There are exactly 2 dogs in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381618", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285996.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_285996", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372475.jpg", "positive_caption": ["There is exactly 1 animal."], "negative_caption": ["There are exactly 3 animals."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2372475", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347026.jpg", "positive_caption": ["There are exactly 2 elephants in the picture."], "negative_caption": ["There are exactly 0 elephants in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347026", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381149.jpg", "positive_caption": ["There are exactly 0 people pictured."], "negative_caption": ["There are exactly 2 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381149", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416045.jpg", "positive_caption": ["There are exactly 3 people in the picture."], "negative_caption": ["There are exactly 0 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416045", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319994.jpg", "positive_caption": ["There is exactly 1 hand seen."], "negative_caption": ["There are exactly 3 hands seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2319994", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402776.jpg", "positive_caption": ["There are exactly 2 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2402776", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410368.jpg", "positive_caption": ["There are exactly 2 fruits."], "negative_caption": ["There are exactly 3 fruits."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2410368", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411400.jpg", "positive_caption": ["There are exactly 2 meals visible."], "negative_caption": ["There are exactly 0 meals visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2411400", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363534.jpg", "positive_caption": ["There are exactly 2 people in the photo."], "negative_caption": ["There are exactly 0 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2363534", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399519.jpg", "positive_caption": ["There is exactly 1 person holding umbrellas."], "negative_caption": ["There are exactly 2 people holding umbrellas."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2399519", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713007.jpg", "positive_caption": ["There are exactly 3 lampposts in the photo."], "negative_caption": ["There is exactly 1 lamppost in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713007", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319169.jpg", "positive_caption": ["There is exactly 1 man."], "negative_caption": ["There are exactly 2 men."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2319169", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363950.jpg", "positive_caption": ["You can distinguish exactly 0 people's faces."], "negative_caption": ["You can distinguish exactly 3 people's faces."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2363950", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316070.jpg", "positive_caption": ["There are exactly 3 loaves."], "negative_caption": ["There is exactly 1 loaf."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2316070", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316044.jpg", "positive_caption": ["There are exactly 0 people riding on elephants."], "negative_caption": ["There is exactly 1 person riding on elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2316044", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363747.jpg", "positive_caption": ["There is exactly 1 racket in the photo."], "negative_caption": ["There are exactly 0 rackets in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2363747", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369707.jpg", "positive_caption": ["There are exactly 2 laptops."], "negative_caption": ["There are exactly 0 laptops."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2369707", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345777.jpg", "positive_caption": ["There is exactly 1 sandwich pictured."], "negative_caption": ["There are exactly 2 sandwiches pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2345777", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353785.jpg", "positive_caption": ["There are exactly 2 glasses on the table."], "negative_caption": ["There are exactly 3 glasses on the table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2353785", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400849.jpg", "positive_caption": ["There are exactly 2 briefcases beside the fireplace."], "negative_caption": ["There are exactly 0 briefcases beside the fireplace."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2400849", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405358.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 2 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2405358", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399258.jpg", "positive_caption": ["Exactly 1 skier can be seen."], "negative_caption": ["Exactly 2 skiers can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2399258", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361081.jpg", "positive_caption": ["There are exactly 2 stuffed animals."], "negative_caption": ["There are exactly 3 stuffed animals."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2361081", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409812.jpg", "positive_caption": ["There are exactly 2 buttons on the baby's shirt."], "negative_caption": ["There is exactly 1 button on the baby's shirt."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2409812", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347396.jpg", "positive_caption": ["There is exactly 1 bike."], "negative_caption": ["There are exactly 2 bikes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347396", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354465.jpg", "positive_caption": ["There are exactly 2 horses."], "negative_caption": ["There are exactly 3 horses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2354465", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346054.jpg", "positive_caption": ["There are exactly 3 wires in the fence."], "negative_caption": ["There are exactly 0 wires in the fence."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2346054", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362228.jpg", "positive_caption": ["There are exactly 2 horses."], "negative_caption": ["There are exactly 0 horses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362228", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362844.jpg", "positive_caption": ["There is exactly 1 bus."], "negative_caption": ["There are exactly 0 buses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362844", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339608.jpg", "positive_caption": ["There are exactly 2 people in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339608", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409703.jpg", "positive_caption": ["There are exactly 2 beds."], "negative_caption": ["There is exactly 1 bed."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2409703", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360527.jpg", "positive_caption": ["There are exactly 2 elephants."], "negative_caption": ["There are exactly 3 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360527", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384714.jpg", "positive_caption": ["There are exactly 3 birds."], "negative_caption": ["There is exactly 1 bird."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2384714", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400622.jpg", "positive_caption": ["There are exactly 2 zebras."], "negative_caption": ["There is exactly 1 zebra."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2400622", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316929.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2316929", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397264.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 3 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397264", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285772.jpg", "positive_caption": ["There are exactly 3 giraffes."], "negative_caption": ["There are exactly 2 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_285772", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_107994.jpg", "positive_caption": ["There are exactly 2 of the cows appear to be standing."], "negative_caption": ["There are exactly 3 of the cows appear to be standing."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_107994", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361928.jpg", "positive_caption": ["There are exactly 2 bears."], "negative_caption": ["There are exactly 3 bears."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2361928", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159858.jpg", "positive_caption": ["There are exactly 3 men in the picture."], "negative_caption": ["There is exactly 1 man in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1159858", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373996.jpg", "positive_caption": ["There is exactly 1 post shown."], "negative_caption": ["There are exactly 2 posts shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2373996", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332353.jpg", "positive_caption": ["There are exactly 3 elephants."], "negative_caption": ["There are exactly 2 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2332353", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401420.jpg", "positive_caption": ["There are exactly 3 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401420", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360453.jpg", "positive_caption": ["There are exactly 2 apples present."], "negative_caption": ["There is exactly 1 apple present."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360453", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323408.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2323408", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396449.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2396449", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373511.jpg", "positive_caption": ["There is exactly 1 person in this picture."], "negative_caption": ["There are exactly 0 people in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2373511", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592671.jpg", "positive_caption": ["There are exactly 2 windows."], "negative_caption": ["There is exactly 1 window."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592671", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377585.jpg", "positive_caption": ["There are exactly 2 wheels."], "negative_caption": ["There are exactly 3 wheels."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2377585", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328557.jpg", "positive_caption": ["There are exactly 3 cars on this train."], "negative_caption": ["There is exactly 1 car on this train."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2328557", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348565.jpg", "positive_caption": ["There is exactly 1 person in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348565", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381422.jpg", "positive_caption": ["There is exactly 1 plane."], "negative_caption": ["There are exactly 0 planes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381422", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326962.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2326962", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360779.jpg", "positive_caption": ["There are exactly 0 people in this photo."], "negative_caption": ["There is exactly 1 person in this photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360779", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372004.jpg", "positive_caption": ["There is exactly 1 bath tub."], "negative_caption": ["There are exactly 0 bath tubs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2372004", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315446.jpg", "positive_caption": ["There is exactly 1 airplane."], "negative_caption": ["There are exactly 2 airplanes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2315446", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361061.jpg", "positive_caption": ["There are exactly 2 road signs."], "negative_caption": ["There are exactly 0 road signs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2361061", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389560.jpg", "positive_caption": ["There is exactly 1 red vase."], "negative_caption": ["There are exactly 3 red vases."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2389560", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403807.jpg", "positive_caption": ["There is exactly 1 round table."], "negative_caption": ["There are exactly 2 round tables."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2403807", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351665.jpg", "positive_caption": ["There are exactly 2 vehicles."], "negative_caption": ["There are exactly 3 vehicles."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2351665", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372537.jpg", "positive_caption": ["There are exactly 3 black boats."], "negative_caption": ["There are exactly 0 black boats."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2372537", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413881.jpg", "positive_caption": ["There are exactly 2 people on the bike."], "negative_caption": ["There is exactly 1 person on the bike."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413881", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336584.jpg", "positive_caption": ["There is exactly 1 person in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336584", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405032.jpg", "positive_caption": ["There are exactly 3 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2405032", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369709.jpg", "positive_caption": ["There are exactly 2 traffic lights."], "negative_caption": ["There are exactly 0 traffic lights."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2369709", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398039.jpg", "positive_caption": ["Exactly 1 chimney can be seen."], "negative_caption": ["Exactly 3 chimneys can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398039", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405893.jpg", "positive_caption": ["There is exactly 1 person sitting in the snow."], "negative_caption": ["There are exactly 3 people sitting in the snow."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2405893", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359364.jpg", "positive_caption": ["There are exactly 2 eyes visible in the photo."], "negative_caption": ["There are exactly 3 eyes visible in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359364", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415650.jpg", "positive_caption": ["There are exactly 2 wheels on the bicycle."], "negative_caption": ["There are exactly 0 wheels on the bicycle."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2415650", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377710.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2377710", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713788.jpg", "positive_caption": ["There are exactly 2 green lights."], "negative_caption": ["There are exactly 3 green lights."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713788", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417726.jpg", "positive_caption": ["There is exactly 1 zebra shown."], "negative_caption": ["There are exactly 3 zebras shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2417726", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394206.jpg", "positive_caption": ["There are exactly 2 people kiteboarding."], "negative_caption": ["There are exactly 1 people kiteboarding."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2394206", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367108.jpg", "positive_caption": ["There are exactly 2 food trucks pictured."], "negative_caption": ["There are exactly 3 food trucks pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367108", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347619.jpg", "positive_caption": ["There are exactly 2 buses in the picture."], "negative_caption": ["There is exactly 1 bus in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347619", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404604.jpg", "positive_caption": ["There is exactly 1 surfer."], "negative_caption": ["There are exactly 2 surfers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2404604", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348755.jpg", "positive_caption": ["There are exactly 2 color tiles."], "negative_caption": ["There are exactly 3 color tiles."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348755", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316517.jpg", "positive_caption": ["There are exactly 2 shoes visible."], "negative_caption": ["There are exactly 0 shoes visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2316517", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388836.jpg", "positive_caption": ["There are exactly 3 containers."], "negative_caption": ["There is exactly 1 container."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2388836", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396563.jpg", "positive_caption": ["There are exactly 3 girls on the table."], "negative_caption": ["There are exactly 2 girls on the table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2396563", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371437.jpg", "positive_caption": ["There are exactly 2 bowls."], "negative_caption": ["There are exactly 0 bowls."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371437", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345859.jpg", "positive_caption": ["There are exactly 2 people shown."], "negative_caption": ["There are exactly 1 people shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2345859", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378673.jpg", "positive_caption": ["There are exactly 2 pillows on the bed."], "negative_caption": ["There are exactly 3 pillows on the bed."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2378673", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409927.jpg", "positive_caption": ["There is exactly 1 plane seen."], "negative_caption": ["There are exactly 3 planes seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2409927", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413520.jpg", "positive_caption": ["There are exactly 2 trees next to the bus."], "negative_caption": ["There are exactly 0 trees next to the bus."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413520", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375522.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2375522", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377654.jpg", "positive_caption": ["There are exactly 3 zebras."], "negative_caption": ["There are exactly 2 zebras."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2377654", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362977.jpg", "positive_caption": ["There is exactly 1 person in this picture."], "negative_caption": ["There are exactly 3 people in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362977", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374891.jpg", "positive_caption": ["You see exactly 1 dog."], "negative_caption": ["You see exactly 2 dogs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2374891", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359816.jpg", "positive_caption": ["Exactly 2 bananas can be seen."], "negative_caption": ["Exactly 3 bananas can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359816", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323471.jpg", "positive_caption": ["There is exactly 1 player."], "negative_caption": ["There are exactly 2 players."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2323471", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357053.jpg", "positive_caption": ["There are exactly 2 elephants in the picture."], "negative_caption": ["There is exactly 1 elephant in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2357053", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330292.jpg", "positive_caption": ["There is exactly 1 train."], "negative_caption": ["There are exactly 2 trains."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2330292", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347510.jpg", "positive_caption": ["There is exactly 1 person in this photo."], "negative_caption": ["There are exactly 2 people in this photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347510", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318981.jpg", "positive_caption": ["There are exactly 0 giraffes."], "negative_caption": ["There are exactly 2 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2318981", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380462.jpg", "positive_caption": ["There are exactly 2 boats shown."], "negative_caption": ["There is exactly 1 boat shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2380462", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344887.jpg", "positive_caption": ["There are exactly 2 clock faces visible."], "negative_caption": ["There is exactly 1 clock face visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2344887", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369750.jpg", "positive_caption": ["There are exactly 3 pieces of furniture in the room."], "negative_caption": ["There are exactly 0 pieces of furniture in the room."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2369750", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352789.jpg", "positive_caption": ["There is exactly 1 person in picture."], "negative_caption": ["There are exactly 0 people in picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2352789", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347649.jpg", "positive_caption": ["There are exactly 2 cats shown."], "negative_caption": ["There are exactly 3 cats shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347649", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324997.jpg", "positive_caption": ["There is exactly 1 computer shown."], "negative_caption": ["There are exactly 2 computers shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2324997", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332064.jpg", "positive_caption": ["There are exactly 2 birds."], "negative_caption": ["There are exactly 3 birds."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2332064", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398149.jpg", "positive_caption": ["There are exactly 3 people in this picture."], "negative_caption": ["There is exactly 1 person in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398149", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316065.jpg", "positive_caption": ["There is exactly 1 man in the air."], "negative_caption": ["There are exactly 2 men in the air."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2316065", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388281.jpg", "positive_caption": ["There are exactly 2 baby elephants on the picture."], "negative_caption": ["There is exactly 1 baby elephant on the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2388281", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324970.jpg", "positive_caption": ["There are exactly 2 toys."], "negative_caption": ["There are exactly 3 toys."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2324970", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322869.jpg", "positive_caption": ["There is exactly 1 computer."], "negative_caption": ["There are exactly 2 computers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2322869", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355975.jpg", "positive_caption": ["There are exactly 3 kinds of fruits on the table."], "negative_caption": ["There are exactly 2 kinds of fruits on the table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2355975", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1160068.jpg", "positive_caption": ["There is exactly 1 bike leaning agains the tree."], "negative_caption": ["There are exactly 0 bikes leaning agains the tree."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1160068", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365038.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2365038", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349442.jpg", "positive_caption": ["There are exactly 3 computers."], "negative_caption": ["There are exactly 2 computers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2349442", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395440.jpg", "positive_caption": ["There is exactly 1 girl in the pic."], "negative_caption": ["There are exactly 2 girls in the pic."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2395440", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392698.jpg", "positive_caption": ["There are exactly 3 giraffes in the picture."], "negative_caption": ["There are exactly 2 giraffes in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2392698", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358703.jpg", "positive_caption": ["There is exactly 1 fire truck in the photo."], "negative_caption": ["There are exactly 2 fire trucks in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2358703", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327497.jpg", "positive_caption": ["There are exactly 2 pillows on the bed."], "negative_caption": ["There are exactly 3 pillows on the bed."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327497", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356455.jpg", "positive_caption": ["There are exactly 3 trees visible."], "negative_caption": ["There is exactly 1 tree visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2356455", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327558.jpg", "positive_caption": ["There are exactly 2 horses."], "negative_caption": ["There is exactly 1 horse."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327558", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348031.jpg", "positive_caption": ["The buses have exactly 2 levels."], "negative_caption": ["The buses have exactly 1 level."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348031", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373190.jpg", "positive_caption": ["There are exactly 0 dogs in the picture."], "negative_caption": ["There are exactly 2 dogs in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2373190", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375658.jpg", "positive_caption": ["There is exactly 1 dog."], "negative_caption": ["There are exactly 2 dogs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2375658", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335474.jpg", "positive_caption": ["There are exactly 3 wheels shown."], "negative_caption": ["There are exactly 2 wheels shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2335474", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317526.jpg", "positive_caption": ["There is exactly 1 brown cow."], "negative_caption": ["There are exactly 2 brown cows."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2317526", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410500.jpg", "positive_caption": ["There is exactly 1 person in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2410500", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340298.jpg", "positive_caption": ["There are exactly 3 motorbikes seen."], "negative_caption": ["There is exactly 1 motorbike seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2340298", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386201.jpg", "positive_caption": ["There are exactly 0 cars on the baseball field."], "negative_caption": ["There are exactly 2 cars on the baseball field."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2386201", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356511.jpg", "positive_caption": ["There are exactly 2 forks."], "negative_caption": ["There is exactly 1 fork."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2356511", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349766.jpg", "positive_caption": ["There is exactly 1 frisbee."], "negative_caption": ["There are exactly 3 frisbees."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2349766", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361792.jpg", "positive_caption": ["There are exactly 3 black cows."], "negative_caption": ["There are exactly 2 black cows."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2361792", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397132.jpg", "positive_caption": ["There are exactly 2 bikes in the picture."], "negative_caption": ["There are exactly 3 bikes in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397132", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389337.jpg", "positive_caption": ["There is exactly 1 woman."], "negative_caption": ["There are exactly 2 women."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2389337", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370023.jpg", "positive_caption": ["There are exactly 2 pens on the desk."], "negative_caption": ["There is exactly 1 pen on the desk."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370023", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409183.jpg", "positive_caption": ["There are exactly 3 lights hanging."], "negative_caption": ["There are exactly 0 lights hanging."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2409183", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375006.jpg", "positive_caption": ["There is exactly 1 train."], "negative_caption": ["There are exactly 0 trains."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2375006", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373248.jpg", "positive_caption": ["There are exactly 2 men in the picture."], "negative_caption": ["There are exactly 3 men in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2373248", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409097.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 2 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2409097", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401200.jpg", "positive_caption": ["There is exactly 1 person skating."], "negative_caption": ["There are exactly 0 people skating."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401200", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387073.jpg", "positive_caption": ["There are exactly 3 lamps pictured here."], "negative_caption": ["There is exactly 1 lamp pictured here."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2387073", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325915.jpg", "positive_caption": ["There is exactly 1 tree with leaves or needles in the picture."], "negative_caption": ["There are exactly 2 trees with leaves or needles in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2325915", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391117.jpg", "positive_caption": ["There are exactly 2 red lights seen."], "negative_caption": ["There is exactly 1 red light seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2391117", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416607.jpg", "positive_caption": ["There is exactly 1 chair."], "negative_caption": ["There are exactly 3 chairs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416607", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363335.jpg", "positive_caption": ["There is exactly 1 mast on the closest boat."], "negative_caption": ["There are exactly 2 masts on the closest boat."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2363335", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370194.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 0 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370194", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159443.jpg", "positive_caption": ["There are exactly 3 old men."], "negative_caption": ["There are exactly 2 old men."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1159443", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336393.jpg", "positive_caption": ["There are exactly 3 street signs."], "negative_caption": ["There are exactly 2 street signs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336393", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362560.jpg", "positive_caption": ["You see exactly 2 of the dog's legs."], "negative_caption": ["You see exactly 1 of the dog's legs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362560", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285699.jpg", "positive_caption": ["There are exactly 2 towels hanging on the stove."], "negative_caption": ["There are exactly 3 towels hanging on the stove."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_285699", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395474.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2395474", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404907.jpg", "positive_caption": ["There are exactly 2 wings."], "negative_caption": ["There are exactly 3 wings."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2404907", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360672.jpg", "positive_caption": ["There are exactly 2 eyes on the elephant."], "negative_caption": ["There are exactly 3 eyes on the elephant."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360672", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412168.jpg", "positive_caption": ["There are exactly 0 windows in the photo."], "negative_caption": ["There are exactly 2 windows in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2412168", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412918.jpg", "positive_caption": ["There are exactly 2 bright pink umbrellas."], "negative_caption": ["There are exactly 3 bright pink umbrellas."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2412918", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393679.jpg", "positive_caption": ["There are exactly 0 animals shown."], "negative_caption": ["There are exactly 3 animals shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2393679", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391801.jpg", "positive_caption": ["There are exactly 2 boats."], "negative_caption": ["There is exactly 1 boat."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2391801", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330593.jpg", "positive_caption": ["There are exactly 2 giraffe shown."], "negative_caption": ["There is exactly 1 giraffe shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2330593", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401567.jpg", "positive_caption": ["There are exactly 3 giraffes facing right."], "negative_caption": ["There are exactly 2 giraffes facing right."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401567", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379882.jpg", "positive_caption": ["There are exactly 2 plant pots by the window."], "negative_caption": ["There is exactly 1 plant pot by the window."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2379882", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363139.jpg", "positive_caption": ["There is exactly 1 giraffe in the scene."], "negative_caption": ["There are exactly 2 giraffes in the scene."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2363139", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329511.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2329511", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342201.jpg", "positive_caption": ["There is exactly 1 bird in the picture."], "negative_caption": ["There are exactly 2 birds in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2342201", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334842.jpg", "positive_caption": ["There are exactly 2 sinks."], "negative_caption": ["There is exactly 1 sink."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334842", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402790.jpg", "positive_caption": ["There are exactly 2 electric meters."], "negative_caption": ["There are exactly 0 electric meters."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2402790", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366156.jpg", "positive_caption": ["There are exactly 2 animals shown."], "negative_caption": ["There are exactly 3 animals shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2366156", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320298.jpg", "positive_caption": ["There is exactly 1 person in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320298", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592171.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592171", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355135.jpg", "positive_caption": ["There are exactly 2 pens on the desk."], "negative_caption": ["There is exactly 1 pen on the desk."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2355135", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401673.jpg", "positive_caption": ["There are exactly 2 bed in the room."], "negative_caption": ["There is exactly 1 bed in the room."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401673", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339624.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339624", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411911.jpg", "positive_caption": ["There are exactly 2 vehicles in the photo."], "negative_caption": ["There are exactly 3 vehicles in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2411911", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349512.jpg", "positive_caption": ["There are exactly 0 people pictured."], "negative_caption": ["There are exactly 2 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2349512", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376885.jpg", "positive_caption": ["There is exactly 1 person in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2376885", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373119.jpg", "positive_caption": ["There are exactly 2 glasses on the table."], "negative_caption": ["There is exactly 1 glass on the table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2373119", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348110.jpg", "positive_caption": ["There are exactly 2 giraffes."], "negative_caption": ["There is exactly 1 giraffe."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348110", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407415.jpg", "positive_caption": ["There are exactly 2 men standing in line for the bus."], "negative_caption": ["There is exactly 1 man standing in line for the bus."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2407415", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321035.jpg", "positive_caption": ["There is exactly 1 window in this room."], "negative_caption": ["There are exactly 2 windows in this room."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2321035", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366250.jpg", "positive_caption": ["There are exactly 3 train carts."], "negative_caption": ["There are exactly 2 train carts."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2366250", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398189.jpg", "positive_caption": ["There are exactly 2 people pictured."], "negative_caption": ["There are exactly 3 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398189", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359425.jpg", "positive_caption": ["There are exactly 0 people pictured."], "negative_caption": ["There are exactly 2 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359425", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332316.jpg", "positive_caption": ["There are exactly 3 sauce."], "negative_caption": ["There is exactly 1 sauce."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2332316", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415424.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2415424", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375288.jpg", "positive_caption": ["There are exactly 2 people in this picture."], "negative_caption": ["There are exactly 0 people in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2375288", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367879.jpg", "positive_caption": ["There are exactly 3 stuffed animals."], "negative_caption": ["There are exactly 2 stuffed animals."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367879", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330133.jpg", "positive_caption": ["There are exactly 0 dogs."], "negative_caption": ["There are exactly 2 dogs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2330133", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370734.jpg", "positive_caption": ["There is exactly 1 plane."], "negative_caption": ["There are exactly 2 planes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370734", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349520.jpg", "positive_caption": ["There are exactly 2 clocks on the building."], "negative_caption": ["There is exactly 1 clock on the building."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2349520", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389210.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2389210", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401397.jpg", "positive_caption": ["There are exactly 2 slices on the sandwich."], "negative_caption": ["There are exactly 3 slices on the sandwich."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401397", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341744.jpg", "positive_caption": ["There are exactly 2 girls."], "negative_caption": ["There is exactly 1 girl."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341744", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407188.jpg", "positive_caption": ["There is exactly 1 lamp in the photo."], "negative_caption": ["There are exactly 0 lamps in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2407188", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328481.jpg", "positive_caption": ["There are exactly 2 beds."], "negative_caption": ["There are exactly 3 beds."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2328481", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358663.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2358663", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372953.jpg", "positive_caption": ["There is exactly 1 child in the image."], "negative_caption": ["There are exactly 3 children in the image."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2372953", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329409.jpg", "positive_caption": ["There are exactly 2 wheels."], "negative_caption": ["There is exactly 1 wheel."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2329409", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398437.jpg", "positive_caption": ["There is exactly 1 white and black horse."], "negative_caption": ["There are exactly 2 white and black horses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398437", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383391.jpg", "positive_caption": ["There is exactly 1 skateboard."], "negative_caption": ["There are exactly 2 skateboards."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2383391", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325780.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2325780", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357093.jpg", "positive_caption": ["There are exactly 3 zebras."], "negative_caption": ["There is exactly 1 zebra."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2357093", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373777.jpg", "positive_caption": ["There are exactly 2 people playing."], "negative_caption": ["There is exactly 1 person playing."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2373777", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344767.jpg", "positive_caption": ["There are exactly 3 trees pictured."], "negative_caption": ["There are exactly 2 trees pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2344767", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360441.jpg", "positive_caption": ["There are exactly 2 busses."], "negative_caption": ["There are exactly 0 busses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360441", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385997.jpg", "positive_caption": ["There is exactly 1 person in this picture."], "negative_caption": ["There are exactly 2 people in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2385997", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355716.jpg", "positive_caption": ["There are exactly 2 bikes in the photo."], "negative_caption": ["There is exactly 1 bike in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2355716", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386633.jpg", "positive_caption": ["There are exactly 2 elephants."], "negative_caption": ["There is exactly 1 elephant."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2386633", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385794.jpg", "positive_caption": ["There is exactly 1 fireplace."], "negative_caption": ["There are exactly 2 fireplaces."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2385794", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411827.jpg", "positive_caption": ["There are exactly 0 people visible."], "negative_caption": ["There are exactly 2 people visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2411827", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376988.jpg", "positive_caption": ["There are exactly 3 children."], "negative_caption": ["There are exactly 2 children."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2376988", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411229.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2411229", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384323.jpg", "positive_caption": ["There is exactly 1 person in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2384323", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416457.jpg", "positive_caption": ["There are exactly 3 pillows."], "negative_caption": ["There are exactly 2 pillows."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416457", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370551.jpg", "positive_caption": ["There is exactly 1 horse."], "negative_caption": ["There are exactly 3 horses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370551", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334188.jpg", "positive_caption": ["There is exactly 1 giraffe shown."], "negative_caption": ["There are exactly 2 giraffes shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334188", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371746.jpg", "positive_caption": ["There are exactly 2 wheels."], "negative_caption": ["There is exactly 1 wheel."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371746", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285840.jpg", "positive_caption": ["There is exactly 1 onion."], "negative_caption": ["There are exactly 2 onions."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_285840", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347856.jpg", "positive_caption": ["Exactly 2 players can be seen."], "negative_caption": ["Exactly 1 player can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347856", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392555.jpg", "positive_caption": ["There are exactly 0 animals in the picture."], "negative_caption": ["There are exactly 2 animals in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2392555", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357556.jpg", "positive_caption": ["There are exactly 2 horses."], "negative_caption": ["There is exactly 1 horse."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2357556", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370167.jpg", "positive_caption": ["There are exactly 3 trains in this image."], "negative_caption": ["There are exactly 0 trains in this image."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370167", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383472.jpg", "positive_caption": ["There is exactly 1 woman."], "negative_caption": ["There are exactly 2 women."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2383472", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340236.jpg", "positive_caption": ["There is exactly 1 baseball player in the picture."], "negative_caption": ["There are exactly 2 baseball players in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2340236", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591933.jpg", "positive_caption": ["There are exactly 3 do not enter signs."], "negative_caption": ["There is exactly 1 do not enter sign."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1591933", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357394.jpg", "positive_caption": ["There are exactly 2 white flags."], "negative_caption": ["There are exactly 3 white flags."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2357394", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397623.jpg", "positive_caption": ["Exactly 2 people can be seen."], "negative_caption": ["Exactly 3 people can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397623", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331907.jpg", "positive_caption": ["There are exactly 2 people visibly wearing hats."], "negative_caption": ["There is exactly 1 person visibly wearing hats."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2331907", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317862.jpg", "positive_caption": ["There are exactly 0 people riding on elephants."], "negative_caption": ["There are exactly 2 people riding on elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2317862", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320148.jpg", "positive_caption": ["There are exactly 2 lights on the car."], "negative_caption": ["There are exactly 3 lights on the car."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320148", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399144.jpg", "positive_caption": ["There is exactly 1 player on the court in this photo."], "negative_caption": ["There are exactly 2 players on the court in this photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2399144", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353432.jpg", "positive_caption": ["There are exactly 2 pillows visible."], "negative_caption": ["There are exactly 3 pillows visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2353432", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321174.jpg", "positive_caption": ["There are exactly 3 giraffes sitting."], "negative_caption": ["There is exactly 1 giraffe sitting."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2321174", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341870.jpg", "positive_caption": ["There are exactly 3 colors on the flag."], "negative_caption": ["There are exactly 2 colors on the flag."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341870", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365871.jpg", "positive_caption": ["There are exactly 3 kites."], "negative_caption": ["There is exactly 1 kite."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2365871", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388750.jpg", "positive_caption": ["There are exactly 2 birds."], "negative_caption": ["There are exactly 3 birds."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2388750", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391215.jpg", "positive_caption": ["There are exactly 0 people in picture."], "negative_caption": ["There are exactly 2 people in picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2391215", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316052.jpg", "positive_caption": ["There are exactly 0 children in the photo."], "negative_caption": ["There is exactly 1 children in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2316052", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327221.jpg", "positive_caption": ["There are exactly 3 toilets."], "negative_caption": ["There are exactly 2 toilets."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327221", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341616.jpg", "positive_caption": ["There are exactly 2 giraffe."], "negative_caption": ["There are exactly 3 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341616", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414112.jpg", "positive_caption": ["There are exactly 2 men in the image wearing hats."], "negative_caption": ["There is exactly 1 man in the image wearing hats."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2414112", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382711.jpg", "positive_caption": ["There are exactly 3 cats in the pictures all together."], "negative_caption": ["There are exactly 2 cats in the pictures all together."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2382711", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326358.jpg", "positive_caption": ["There is exactly 1 toilet in the picture."], "negative_caption": ["There are exactly 3 toilets in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2326358", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339398.jpg", "positive_caption": ["There are exactly 2 benches."], "negative_caption": ["There are exactly 3 benches."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339398", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285977.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_285977", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408967.jpg", "positive_caption": ["There is exactly 1 cooler in the photo."], "negative_caption": ["There are exactly 3 coolers in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2408967", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359263.jpg", "positive_caption": ["There are exactly 3 people in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359263", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390501.jpg", "positive_caption": ["There are exactly 2 swans."], "negative_caption": ["There are exactly 3 swans."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2390501", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417283.jpg", "positive_caption": ["There are exactly 2 giraffe."], "negative_caption": ["There are exactly 0 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2417283", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325721.jpg", "positive_caption": ["There is exactly 1 building."], "negative_caption": ["There are exactly 2 buildings."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2325721", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329142.jpg", "positive_caption": ["There are exactly 3 stars in the tattoo."], "negative_caption": ["There are exactly 2 stars in the tattoo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2329142", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354762.jpg", "positive_caption": ["There are exactly 3 stained glass windows."], "negative_caption": ["There are exactly 2 stained glass windows."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2354762", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396896.jpg", "positive_caption": ["There is exactly 1 bird."], "negative_caption": ["There are exactly 2 birds."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2396896", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353431.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 2 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2353431", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713030.jpg", "positive_caption": ["There are exactly 3 people on the motorcycle."], "negative_caption": ["There is exactly 1 person on the motorcycle."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713030", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334470.jpg", "positive_caption": ["There are exactly 3 snowboards in the photo."], "negative_caption": ["There are exactly 2 snowboards in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334470", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412770.jpg", "positive_caption": ["There is exactly 1 person skiing."], "negative_caption": ["There are exactly 2 people skiing."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2412770", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713291.jpg", "positive_caption": ["We can see exactly 1 jump."], "negative_caption": ["We can see exactly 2 jumps."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713291", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391564.jpg", "positive_caption": ["There are exactly 3 motorbikes in the photo."], "negative_caption": ["There is exactly 1 motorbike in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2391564", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386539.jpg", "positive_caption": ["There is exactly 1 piece on the plate."], "negative_caption": ["There are exactly 0 pieces on the plate."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2386539", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398450.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398450", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342103.jpg", "positive_caption": ["There are exactly 2 pieces of paper."], "negative_caption": ["There are exactly 3 pieces of paper."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2342103", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386104.jpg", "positive_caption": ["There are exactly 2 traffic lights in the picture."], "negative_caption": ["There are exactly 1 traffic lights in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2386104", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324562.jpg", "positive_caption": ["There are exactly 2 towels."], "negative_caption": ["There is exactly 1 towel."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2324562", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356169.jpg", "positive_caption": ["There are exactly 2 gray bowls on the counter."], "negative_caption": ["There is exactly 1 gray bowl on the counter."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2356169", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391207.jpg", "positive_caption": ["There are exactly 2 clocks pictured."], "negative_caption": ["There is exactly 1 clock pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2391207", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416757.jpg", "positive_caption": ["There are exactly 2 sausage links pictured."], "negative_caption": ["There are exactly 0 sausage links pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416757", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415217.jpg", "positive_caption": ["There is exactly 1 snowboarder."], "negative_caption": ["There are exactly 3 snowboarders."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2415217", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353185.jpg", "positive_caption": ["There are exactly 2 people shown skateboarding."], "negative_caption": ["There are exactly 3 people shown skateboarding."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2353185", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335719.jpg", "positive_caption": ["There is exactly 1 man at the beach."], "negative_caption": ["There are exactly 3 men at the beach."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2335719", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369922.jpg", "positive_caption": ["There are exactly 2 doors on the fridge."], "negative_caption": ["There is exactly 1 door on the fridge."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2369922", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372856.jpg", "positive_caption": ["Exactly 1 of the men have hats."], "negative_caption": ["Exactly 2 of the men have hats."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2372856", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358002.jpg", "positive_caption": ["There are exactly 2 men playing the game."], "negative_caption": ["There is exactly 1 man playing the game."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2358002", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498410.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_498410", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406625.jpg", "positive_caption": ["There are exactly 2 people in the water."], "negative_caption": ["There are exactly 0 people in the water."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2406625", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332797.jpg", "positive_caption": ["There is exactly 1 person in the air."], "negative_caption": ["There are exactly 2 people in the air."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2332797", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414337.jpg", "positive_caption": ["There are exactly 0 lamps on the table."], "negative_caption": ["There are exactly 3 lamps on the table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2414337", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394230.jpg", "positive_caption": ["There is exactly 1 zebra laying down."], "negative_caption": ["There are exactly 2 zebras laying down."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2394230", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333972.jpg", "positive_caption": ["There is exactly 1 skier."], "negative_caption": ["There are exactly 2 skiers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2333972", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416564.jpg", "positive_caption": ["There is exactly 1 bird in the picture."], "negative_caption": ["There are exactly 2 birds in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416564", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328435.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2328435", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389378.jpg", "positive_caption": ["There is exactly 1 vase in the picture."], "negative_caption": ["There are exactly 2 vases in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2389378", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354092.jpg", "positive_caption": ["There is exactly 1 sink."], "negative_caption": ["There are exactly 3 sinks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2354092", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334394.jpg", "positive_caption": ["There is exactly 1 clock."], "negative_caption": ["There are exactly 2 clocks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334394", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392355.jpg", "positive_caption": ["There are exactly 2 girls shown."], "negative_caption": ["There are exactly 3 girls shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2392355", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386307.jpg", "positive_caption": ["There is exactly 1 man pictured."], "negative_caption": ["There are exactly 2 men pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2386307", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344947.jpg", "positive_caption": ["There are exactly 2 windows."], "negative_caption": ["There are exactly 3 windows."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2344947", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385362.jpg", "positive_caption": ["There is exactly 1 person pictured."], "negative_caption": ["There are exactly 3 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2385362", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398610.jpg", "positive_caption": ["There is exactly 1 fan."], "negative_caption": ["There are exactly 3 fans."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398610", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319339.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2319339", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401859.jpg", "positive_caption": ["There are exactly 3 birds."], "negative_caption": ["There is exactly 1 bird."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401859", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338334.jpg", "positive_caption": ["There are exactly 2 teddy bears."], "negative_caption": ["There are exactly 3 teddy bears."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2338334", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348532.jpg", "positive_caption": ["There is exactly 1 train on the tracks."], "negative_caption": ["There are exactly 2 trains on the tracks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348532", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159420.jpg", "positive_caption": ["There is exactly 1 person wearing glasses."], "negative_caption": ["There are exactly 2 people wearing glasses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1159420", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498216.jpg", "positive_caption": ["There are exactly 2 people playing."], "negative_caption": ["There are exactly 3 people playing."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_498216", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371241.jpg", "positive_caption": ["There are exactly 2 vegetables green."], "negative_caption": ["There is exactly 1 vegetable green."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371241", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410362.jpg", "positive_caption": ["There are exactly 3 men in this photograph."], "negative_caption": ["There is exactly 1 man in this photograph."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2410362", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414148.jpg", "positive_caption": ["There is exactly 1 suv in view."], "negative_caption": ["There are exactly 3 SUVs in view."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2414148", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381056.jpg", "positive_caption": ["There is exactly 1 trash can."], "negative_caption": ["There are exactly 2 trash cans."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381056", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371495.jpg", "positive_caption": ["There is exactly 1 person in this picture."], "negative_caption": ["There are exactly 3 people in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371495", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315451.jpg", "positive_caption": ["There are exactly 2 carrots being served."], "negative_caption": ["There is exactly 1 carrot being served."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2315451", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380419.jpg", "positive_caption": ["There are exactly 3 cows in the picture."], "negative_caption": ["There is exactly 1 cow in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2380419", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370238.jpg", "positive_caption": ["There are exactly 3 cars."], "negative_caption": ["There is exactly 1 car."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370238", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317060.jpg", "positive_caption": ["There are exactly 2 figurines."], "negative_caption": ["There is exactly 1 figurine."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2317060", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413543.jpg", "positive_caption": ["There are exactly 3 surfboards."], "negative_caption": ["There is exactly 1 surfboard."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413543", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395971.jpg", "positive_caption": ["There is exactly 1 animal in this picture."], "negative_caption": ["There are exactly 2 animals in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2395971", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409286.jpg", "positive_caption": ["There are exactly 2 men."], "negative_caption": ["There are exactly 3 men."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2409286", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394330.jpg", "positive_caption": ["There is exactly 1 stove."], "negative_caption": ["There are exactly 0 stoves."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2394330", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338754.jpg", "positive_caption": ["There is exactly 1 elephant in the picture."], "negative_caption": ["There are exactly 2 elephants in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2338754", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350189.jpg", "positive_caption": ["There are exactly 2 pickles in this picture."], "negative_caption": ["There are exactly 0 pickles in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2350189", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326226.jpg", "positive_caption": ["There are exactly 3 windows visible."], "negative_caption": ["There is exactly 1 window visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2326226", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366329.jpg", "positive_caption": ["There are exactly 2 people in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2366329", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326795.jpg", "positive_caption": ["There is exactly 1 bear in the picture."], "negative_caption": ["There are exactly 3 bears in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2326795", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320619.jpg", "positive_caption": ["You see exactly 1 light."], "negative_caption": ["You see exactly 2 lights."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320619", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362825.jpg", "positive_caption": ["There is exactly 1 woman."], "negative_caption": ["There are exactly 2 women."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362825", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367070.jpg", "positive_caption": ["There are exactly 2 lights seen."], "negative_caption": ["There are exactly 3 lights seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367070", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327762.jpg", "positive_caption": ["There is exactly 1 teddy bear."], "negative_caption": ["There are exactly 3 teddy bears."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327762", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371443.jpg", "positive_caption": ["There is exactly 1 skateboarder in the picture."], "negative_caption": ["There are exactly 2 skateboarders in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371443", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362172.jpg", "positive_caption": ["There are exactly 2 signs."], "negative_caption": ["There are exactly 3 signs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362172", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392242.jpg", "positive_caption": ["There are exactly 2 pieces of meat."], "negative_caption": ["There are exactly 3 pieces of meat."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2392242", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360550.jpg", "positive_caption": ["There is exactly 1 walking sign shown."], "negative_caption": ["There are exactly 0 walking signs shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360550", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395492.jpg", "positive_caption": ["There is exactly 1 slice."], "negative_caption": ["There are exactly 2 slices."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2395492", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383300.jpg", "positive_caption": ["There are exactly 3 giraffes."], "negative_caption": ["There is exactly 1 giraffe."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2383300", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_61601.jpg", "positive_caption": ["There are exactly 0 clouds in the sky."], "negative_caption": ["There are exactly 2 clouds in the sky."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_61601", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341114.jpg", "positive_caption": ["There are exactly 0 dogs in the photo."], "negative_caption": ["There is exactly 1 dog in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341114", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1160125.jpg", "positive_caption": ["There is exactly 1 bus."], "negative_caption": ["There are exactly 2 buses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1160125", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403756.jpg", "positive_caption": ["There are exactly 3 lights above the sink."], "negative_caption": ["There are exactly 2 lights above the sink."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2403756", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335424.jpg", "positive_caption": ["There are exactly 2 pictures on the walls."], "negative_caption": ["There is exactly 1 picture on the walls."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2335424", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335222.jpg", "positive_caption": ["There are exactly 2 ears on the bears head."], "negative_caption": ["There are exactly 0 ears on the bears head."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2335222", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377572.jpg", "positive_caption": ["There is exactly 1 boy in the photo."], "negative_caption": ["There are exactly 2 boys in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2377572", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321003.jpg", "positive_caption": ["There is exactly 1 man in the photo."], "negative_caption": ["There are exactly 0 men in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2321003", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416008.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416008", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339241.jpg", "positive_caption": ["There is exactly 1 cake they cutting."], "negative_caption": ["There are exactly 2 cakes they cutting."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339241", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374913.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2374913", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357832.jpg", "positive_caption": ["There are exactly 3 pieces of pizza."], "negative_caption": ["There are exactly 0 pieces of pizza."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2357832", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316478.jpg", "positive_caption": ["There are exactly 2 vehicles."], "negative_caption": ["There are exactly 0 vehicles."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2316478", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394464.jpg", "positive_caption": ["Exactly 1 person can be seen."], "negative_caption": ["Exactly 2 people can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2394464", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353383.jpg", "positive_caption": ["There are exactly 2 candles on the dining table."], "negative_caption": ["There is exactly 1 candle on the dining table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2353383", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379574.jpg", "positive_caption": ["There is exactly 1 bear."], "negative_caption": ["There are exactly 2 bears."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2379574", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415520.jpg", "positive_caption": ["There are exactly 2 people wearing red and white caps."], "negative_caption": ["There is exactly 1 person wearing red and white caps."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2415520", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380327.jpg", "positive_caption": ["There is exactly 1 donut."], "negative_caption": ["There are exactly 2 donuts."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2380327", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348535.jpg", "positive_caption": ["There are exactly 2 eggs."], "negative_caption": ["There are exactly 0 eggs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348535", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399897.jpg", "positive_caption": ["There is exactly 1 flower."], "negative_caption": ["There are exactly 3 flowers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2399897", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406472.jpg", "positive_caption": ["There are exactly 3 trees."], "negative_caption": ["There is exactly 1 tree."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2406472", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385454.jpg", "positive_caption": ["There is exactly 1 motorcycle."], "negative_caption": ["There are exactly 2 motorcycles."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2385454", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371044.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371044", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376026.jpg", "positive_caption": ["There are exactly 2 traffic lights in the photo."], "negative_caption": ["There is exactly 1 traffic light in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2376026", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409855.jpg", "positive_caption": ["There is exactly 1 person in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2409855", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409615.jpg", "positive_caption": ["There are exactly 2 people riding an elephant."], "negative_caption": ["There are exactly 0 people riding an elephant."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2409615", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408920.jpg", "positive_caption": ["There are exactly 3 people in the picture."], "negative_caption": ["There are exactly 0 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2408920", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412584.jpg", "positive_caption": ["There are exactly 2 lamps."], "negative_caption": ["There are exactly 1 lamps."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2412584", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321751.jpg", "positive_caption": ["There are exactly 2 players."], "negative_caption": ["There are exactly 0 players."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2321751", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329952.jpg", "positive_caption": ["There is exactly 1 player shown."], "negative_caption": ["There are exactly 2 players shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2329952", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367700.jpg", "positive_caption": ["There is exactly 1 flower pot."], "negative_caption": ["There are exactly 2 flower pots."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367700", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321947.jpg", "positive_caption": ["There is exactly 1 piece of cake on the cake."], "negative_caption": ["There are exactly 3 pieces of cake on the cake."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2321947", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382462.jpg", "positive_caption": ["There is exactly 1 truck."], "negative_caption": ["There are exactly 2 trucks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2382462", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348994.jpg", "positive_caption": ["There is exactly 1 guy skating."], "negative_caption": ["There are exactly 2 guys skating."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348994", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365369.jpg", "positive_caption": ["There are exactly 3 umbrellas shown."], "negative_caption": ["There are exactly 2 umbrellas shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2365369", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_286044.jpg", "positive_caption": ["There are exactly 3 people sitting."], "negative_caption": ["There are exactly 2 people sitting."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_286044", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362587.jpg", "positive_caption": ["Exactly 1 player can be seen."], "negative_caption": ["Exactly 3 players can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362587", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327241.jpg", "positive_caption": ["There are exactly 2 people shown."], "negative_caption": ["There are exactly 0 people shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327241", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713612.jpg", "positive_caption": ["There are exactly 3 bikes."], "negative_caption": ["There are exactly 2 bikes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713612", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348316.jpg", "positive_caption": ["There is exactly 1 red loofah."], "negative_caption": ["There are exactly 3 red loofahs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348316", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374547.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2374547", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317344.jpg", "positive_caption": ["There are exactly 3 shelves."], "negative_caption": ["There is exactly 1 shelf."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2317344", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400030.jpg", "positive_caption": ["There are exactly 2 women."], "negative_caption": ["There is exactly 1 woman."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2400030", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359468.jpg", "positive_caption": ["There are exactly 0 clowns in the photo."], "negative_caption": ["There are exactly 3 clowns in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359468", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382115.jpg", "positive_caption": ["There are exactly 2 giraffes."], "negative_caption": ["There are exactly 3 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2382115", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332019.jpg", "positive_caption": ["There is exactly 1 different type of animals in this picture."], "negative_caption": ["There are exactly 3 different types of animals in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2332019", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374119.jpg", "positive_caption": ["There is exactly 1 cat."], "negative_caption": ["There are exactly 2 cats."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2374119", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346859.jpg", "positive_caption": ["The tennis player has exactly 1 leg on the court."], "negative_caption": ["The tennis player has exactly 2 legs on the court."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2346859", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337411.jpg", "positive_caption": ["There are exactly 3 urinals."], "negative_caption": ["There is exactly 1 urinal."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2337411", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337656.jpg", "positive_caption": ["There is exactly 1 sewing machine in the photo."], "negative_caption": ["There are exactly 2 sewing machines in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2337656", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344544.jpg", "positive_caption": ["There is exactly 1 catcher."], "negative_caption": ["There are exactly 2 catchers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2344544", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343940.jpg", "positive_caption": ["There are exactly 2 parking meters visible in the scene."], "negative_caption": ["There are exactly 0 parking meters visible in the scene."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2343940", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364864.jpg", "positive_caption": ["There is exactly 1 ball."], "negative_caption": ["There are exactly 2 balls."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2364864", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398521.jpg", "positive_caption": ["There are exactly 3 tracks."], "negative_caption": ["There are exactly 2 tracks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398521", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341715.jpg", "positive_caption": ["There are exactly 3 chairs in there."], "negative_caption": ["There are exactly 2 chairs in there."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341715", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334456.jpg", "positive_caption": ["There is exactly 1 train track."], "negative_caption": ["There are exactly 3 train tracks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334456", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380634.jpg", "positive_caption": ["There is exactly 1 boat."], "negative_caption": ["There are exactly 0 boats."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2380634", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387504.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2387504", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393320.jpg", "positive_caption": ["There is exactly 1 clock in the picture."], "negative_caption": ["There are exactly 3 clocks in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2393320", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364723.jpg", "positive_caption": ["Exactly 2 men have glasses."], "negative_caption": ["Exactly 3 men have glasses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2364723", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392312.jpg", "positive_caption": ["There are exactly 0 people in the bathroom."], "negative_caption": ["There are exactly 2 people in the bathroom."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2392312", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383064.jpg", "positive_caption": ["There are exactly 2 doors on the bus."], "negative_caption": ["There are exactly 3 doors on the bus."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2383064", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396880.jpg", "positive_caption": ["There is exactly 1 person in the photo."], "negative_caption": ["There are exactly 3 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2396880", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362804.jpg", "positive_caption": ["There is exactly 1 dog."], "negative_caption": ["There are exactly 3 dogs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362804", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341809.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341809", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407816.jpg", "positive_caption": ["There are exactly 3 power lines."], "negative_caption": ["There is exactly 1 power line."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2407816", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336204.jpg", "positive_caption": ["There are exactly 2 birds."], "negative_caption": ["There is exactly 1 bird."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336204", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397921.jpg", "positive_caption": ["There are exactly 2 tomatoes."], "negative_caption": ["There is exactly 1 tomato."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397921", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320439.jpg", "positive_caption": ["Exactly 3 levels of shelves can be seen in the picture."], "negative_caption": ["Exactly 0 levels of shelves can be seen in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320439", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359675.jpg", "positive_caption": ["There are exactly 3 pizzas shown."], "negative_caption": ["There are exactly 2 pizzas shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359675", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359546.jpg", "positive_caption": ["There are exactly 2 people in the photograph."], "negative_caption": ["There are exactly 0 people in the photograph."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359546", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324398.jpg", "positive_caption": ["There is exactly 1 person pictured."], "negative_caption": ["There are exactly 2 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2324398", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348851.jpg", "positive_caption": ["There is exactly 1 cupcake shown."], "negative_caption": ["There are exactly 2 cupcakes shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348851", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349485.jpg", "positive_caption": ["There is exactly 1 banana."], "negative_caption": ["There are exactly 2 bananas."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2349485", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339428.jpg", "positive_caption": ["There are exactly 0 elephants pictured."], "negative_caption": ["There are exactly 2 elephants pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339428", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354118.jpg", "positive_caption": ["There are exactly 2 giraffe in the park."], "negative_caption": ["There is exactly 1 giraffe in the park."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2354118", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159496.jpg", "positive_caption": ["There are exactly 3 train tracks in the photo."], "negative_caption": ["There is exactly 1 train track in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1159496", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360535.jpg", "positive_caption": ["There is exactly 1 motorcycle in the picture."], "negative_caption": ["There are exactly 0 motorcycles in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360535", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343459.jpg", "positive_caption": ["There are exactly 2 plates."], "negative_caption": ["There is exactly 1 plate."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2343459", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327132.jpg", "positive_caption": ["There are exactly 2 people pictured."], "negative_caption": ["There is exactly 1 person pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327132", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322340.jpg", "positive_caption": ["There are exactly 2 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2322340", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359385.jpg", "positive_caption": ["There is exactly 1 bulb shown."], "negative_caption": ["There are exactly 3 bulbs shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359385", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326282.jpg", "positive_caption": ["There are exactly 0 people sitting on the sofa."], "negative_caption": ["There is exactly 1 person sitting on the sofa."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2326282", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326014.jpg", "positive_caption": ["There is exactly 1 man."], "negative_caption": ["There are exactly 2 men."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2326014", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343416.jpg", "positive_caption": ["There are exactly 3 cups in the picture."], "negative_caption": ["There are exactly 2 cups in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2343416", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395156.jpg", "positive_caption": ["Exactly 2 doors can be seen on the first car."], "negative_caption": ["Exactly 1 door can be seen on the first car."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2395156", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393243.jpg", "positive_caption": ["There are exactly 3 birds."], "negative_caption": ["There are exactly 2 birds."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2393243", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331220.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2331220", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371128.jpg", "positive_caption": ["There is exactly 1 chair."], "negative_caption": ["There are exactly 2 chairs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371128", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414344.jpg", "positive_caption": ["There are exactly 2 wheels on the bike."], "negative_caption": ["There is exactly 1 wheel on the bike."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2414344", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401216.jpg", "positive_caption": ["There is exactly 1 person snowboarding."], "negative_caption": ["There are exactly 2 people snowboarding."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401216", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323000.jpg", "positive_caption": ["There is exactly 1 bread."], "negative_caption": ["There are exactly 2 breads."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2323000", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394557.jpg", "positive_caption": ["There are exactly 0 people in this photo."], "negative_caption": ["There is exactly 1 person in this photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2394557", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371124.jpg", "positive_caption": ["There are exactly 2 kids shown."], "negative_caption": ["There are exactly 3 kids shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371124", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315802.jpg", "positive_caption": ["There are exactly 3 leaves on the flatbread."], "negative_caption": ["There are exactly 2 leaves on the flatbread."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2315802", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340825.jpg", "positive_caption": ["There are exactly 2 pans."], "negative_caption": ["There is exactly 1 pan."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2340825", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367094.jpg", "positive_caption": ["There are exactly 2 children."], "negative_caption": ["There is exactly 1 child."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367094", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402837.jpg", "positive_caption": ["There are exactly 2 wine glasses."], "negative_caption": ["There is exactly 1 wine glass."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2402837", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413090.jpg", "positive_caption": ["There are exactly 2 lamps in the picture."], "negative_caption": ["There is exactly 1 lamp in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413090", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362750.jpg", "positive_caption": ["There is exactly 1 person pictured."], "negative_caption": ["There are exactly 2 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362750", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150518.jpg", "positive_caption": ["There are exactly 3 men standing in front of the elephant."], "negative_caption": ["There is exactly 1 man standing in front of the elephant."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_150518", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337483.jpg", "positive_caption": ["There are exactly 0 people on the platform."], "negative_caption": ["There are exactly 2 people on the platform."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2337483", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357803.jpg", "positive_caption": ["There are exactly 3 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2357803", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405436.jpg", "positive_caption": ["There are exactly 2 computer screens."], "negative_caption": ["There are exactly 3 computer screens."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2405436", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396542.jpg", "positive_caption": ["There is exactly 1 elephant in the picture."], "negative_caption": ["There are exactly 3 elephants in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2396542", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399592.jpg", "positive_caption": ["There is exactly 1 roll of tissue."], "negative_caption": ["There are exactly 0 rolls of tissue."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2399592", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360050.jpg", "positive_caption": ["There is exactly 1 train in the picture."], "negative_caption": ["There are exactly 3 trains in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360050", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381918.jpg", "positive_caption": ["There are exactly 3 people shown."], "negative_caption": ["There is exactly 1 person shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381918", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341293.jpg", "positive_caption": ["There is exactly 1 woman in this picture."], "negative_caption": ["There are exactly 2 women in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341293", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404128.jpg", "positive_caption": ["There is exactly 1 clock shown."], "negative_caption": ["There are exactly 2 clocks shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2404128", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412162.jpg", "positive_caption": ["You see exactly 0 people in the bus."], "negative_caption": ["You see exactly 1 person in the bus."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2412162", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358558.jpg", "positive_caption": ["There is exactly 1 bear."], "negative_caption": ["There are exactly 2 bears."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2358558", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368996.jpg", "positive_caption": ["There are exactly 2 eyes of the bird in the photo."], "negative_caption": ["There are exactly 3 eyes of the bird in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2368996", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334324.jpg", "positive_caption": ["There are exactly 0 stars."], "negative_caption": ["There are exactly 2 stars."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334324", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370229.jpg", "positive_caption": ["There are exactly 3 boys shown."], "negative_caption": ["There is exactly 1 boy shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370229", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336172.jpg", "positive_caption": ["There are exactly 0 animals pictured."], "negative_caption": ["There are exactly 3 animals pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336172", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338932.jpg", "positive_caption": ["Exactly 3 large slabs of concrete can be counted."], "negative_caption": ["Exactly 1 large slab of concrete can be counted."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2338932", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346232.jpg", "positive_caption": ["There are exactly 3 sheep."], "negative_caption": ["There are exactly 2 sheep."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2346232", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159742.jpg", "positive_caption": ["There is exactly 1 man holding a shopping back walks on the sidewalk."], "negative_caption": ["There are exactly 2 men holding a shopping back walks on the sidewalk."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1159742", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378819.jpg", "positive_caption": ["There are exactly 2 wheels in this picture."], "negative_caption": ["There are exactly 3 wheels in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2378819", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285645.jpg", "positive_caption": ["There is exactly 1 clock in the photo."], "negative_caption": ["There are exactly 3 clocks in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_285645", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397489.jpg", "positive_caption": ["There is exactly 1 catcher."], "negative_caption": ["There are exactly 2 catchers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397489", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365625.jpg", "positive_caption": ["There are exactly 3 zebras."], "negative_caption": ["There is exactly 1 zebra."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2365625", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365510.jpg", "positive_caption": ["There are exactly 2 dogs in the water."], "negative_caption": ["There is exactly 1 dog in the water."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2365510", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319561.jpg", "positive_caption": ["There is exactly 1 horse."], "negative_caption": ["There are exactly 2 horses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2319561", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318972.jpg", "positive_caption": ["There are exactly 2 buses."], "negative_caption": ["There are exactly 3 buses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2318972", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391488.jpg", "positive_caption": ["There is exactly 1 dog in the picture."], "negative_caption": ["There are exactly 0 dogs in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2391488", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353145.jpg", "positive_caption": ["There are exactly 2 zebras."], "negative_caption": ["There is exactly 1 zebra."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2353145", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327499.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327499", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318931.jpg", "positive_caption": ["There is exactly 1 clock in the photo."], "negative_caption": ["There are exactly 2 clocks in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2318931", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396764.jpg", "positive_caption": ["There are exactly 2 men."], "negative_caption": ["There is exactly 1 man."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2396764", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388937.jpg", "positive_caption": ["The man sitting on the rail has exactly 2 shoes on."], "negative_caption": ["The man sitting on the rail has exactly 1 shoe on."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2388937", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328260.jpg", "positive_caption": ["There are exactly 2 people shown."], "negative_caption": ["There is exactly 1 person shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2328260", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393882.jpg", "positive_caption": ["There are exactly 2 lights behind the counter."], "negative_caption": ["There is exactly 1 light behind the counter."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2393882", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713618.jpg", "positive_caption": ["There are exactly 2 buses."], "negative_caption": ["There is exactly 1 bus."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713618", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592001.jpg", "positive_caption": ["There are exactly 2 glasses on the table."], "negative_caption": ["There are exactly 0 glasses on the table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592001", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411900.jpg", "positive_caption": ["There are exactly 3 animals."], "negative_caption": ["There are exactly 0 animals."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2411900", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416712.jpg", "positive_caption": ["There is exactly 1 elephant here."], "negative_caption": ["There are exactly 2 elephants here."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416712", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373151.jpg", "positive_caption": ["There are exactly 3 of the animals giraffes."], "negative_caption": ["There is exactly 1 of the animals giraffe."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2373151", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329018.jpg", "positive_caption": ["There are exactly 3 traffic lights."], "negative_caption": ["There are exactly 2 traffic lights."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2329018", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376048.jpg", "positive_caption": ["There are exactly 2 animals in the image."], "negative_caption": ["There is exactly 1 animal in the image."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2376048", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337387.jpg", "positive_caption": ["There are exactly 0 people pictured."], "negative_caption": ["There is exactly 1 person pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2337387", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374559.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2374559", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321320.jpg", "positive_caption": ["There are exactly 2 tables."], "negative_caption": ["There are exactly 3 tables."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2321320", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414645.jpg", "positive_caption": ["There is exactly 1 hydrant."], "negative_caption": ["There are exactly 3 hydrants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2414645", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373325.jpg", "positive_caption": ["There are exactly 3 pieces of meat."], "negative_caption": ["There are exactly 2 pieces of meat."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2373325", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413663.jpg", "positive_caption": ["There is exactly 1 hand."], "negative_caption": ["There are exactly 3 hands."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413663", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387440.jpg", "positive_caption": ["There are exactly 0 humans in the picture."], "negative_caption": ["There is exactly 1 human in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2387440", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361499.jpg", "positive_caption": ["There are exactly 2 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2361499", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345801.jpg", "positive_caption": ["There are exactly 0 animals."], "negative_caption": ["There is exactly 1 animal."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2345801", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416665.jpg", "positive_caption": ["There is exactly 1 bike."], "negative_caption": ["There are exactly 2 bikes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416665", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330797.jpg", "positive_caption": ["There are exactly 2 cars."], "negative_caption": ["There are exactly 0 cars."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2330797", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370171.jpg", "positive_caption": ["There is exactly 1 elephant."], "negative_caption": ["There are exactly 3 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370171", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387910.jpg", "positive_caption": ["There is exactly 1 bird."], "negative_caption": ["There are exactly 3 birds."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2387910", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320272.jpg", "positive_caption": ["There are exactly 2 trees in the picture."], "negative_caption": ["There is exactly 1 tree in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320272", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375472.jpg", "positive_caption": ["There are exactly 2 blocks of ice."], "negative_caption": ["There are exactly 3 blocks of ice."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2375472", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399454.jpg", "positive_caption": ["There are exactly 2 donuts on the plate."], "negative_caption": ["There are exactly 0 donuts on the plate."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2399454", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341939.jpg", "positive_caption": ["There are exactly 3 boys playing frisbee."], "negative_caption": ["There is exactly 1 boy playing frisbee."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341939", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410093.jpg", "positive_caption": ["There is exactly 1 elephant."], "negative_caption": ["There are exactly 0 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2410093", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400639.jpg", "positive_caption": ["There is exactly 1 train pictured."], "negative_caption": ["There are exactly 3 trains pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2400639", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336833.jpg", "positive_caption": ["There are exactly 2 street names written."], "negative_caption": ["There are exactly 3 street names written."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336833", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334865.jpg", "positive_caption": ["There are exactly 2 cars."], "negative_caption": ["There are exactly 3 cars."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334865", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385627.jpg", "positive_caption": ["There are exactly 3 horses shown."], "negative_caption": ["There are exactly 2 horses shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2385627", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366204.jpg", "positive_caption": ["There are exactly 3 people in this photo."], "negative_caption": ["There are exactly 0 people in this photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2366204", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405077.jpg", "positive_caption": ["There is exactly 1 safety cone visible."], "negative_caption": ["There are exactly 2 safety cones visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2405077", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389464.jpg", "positive_caption": ["There are exactly 3 kites."], "negative_caption": ["There are exactly 2 kites."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2389464", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498360.jpg", "positive_caption": ["There are exactly 2 poles hold up the gate."], "negative_caption": ["There are exactly 0 poles hold up the gate."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_498360", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327199.jpg", "positive_caption": ["There are exactly 2 white replacement tiles seen."], "negative_caption": ["There are exactly 0 white replacement tiles seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327199", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365140.jpg", "positive_caption": ["There are exactly 3 San Francisco players on the field."], "negative_caption": ["There are exactly 2 San Francisco players on the field."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2365140", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411461.jpg", "positive_caption": ["There are exactly 2 men standing by the bus."], "negative_caption": ["There is exactly 1 man standing by the bus."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2411461", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414366.jpg", "positive_caption": ["There are exactly 3 train cars."], "negative_caption": ["There are exactly 1 train cars."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2414366", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330997.jpg", "positive_caption": ["There are exactly 2 slices of pizza on the plate."], "negative_caption": ["There are exactly 1 slices of pizza on the plate."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2330997", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388736.jpg", "positive_caption": ["There is exactly 1 bench in the picture."], "negative_caption": ["There are exactly 3 benches in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2388736", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320400.jpg", "positive_caption": ["There is exactly 1 woman visible in the photo."], "negative_caption": ["There are exactly 2 women visible in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320400", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401335.jpg", "positive_caption": ["There are exactly 3 wall sconces visible in this picture."], "negative_caption": ["There is exactly 1 wall sconce visible in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401335", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359143.jpg", "positive_caption": ["There is exactly 1 drink visible."], "negative_caption": ["There are exactly 2 drinks visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359143", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331282.jpg", "positive_caption": ["There are exactly 2 people sitting on the motorcycles."], "negative_caption": ["There are exactly 0 people sitting on the motorcycles."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2331282", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413242.jpg", "positive_caption": ["There is exactly 1 burger."], "negative_caption": ["There are exactly 2 burgers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413242", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413171.jpg", "positive_caption": ["There are exactly 3 people seen in the photo."], "negative_caption": ["There is exactly 1 person seen in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413171", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408965.jpg", "positive_caption": ["There are exactly 2 men."], "negative_caption": ["There are exactly 3 men."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2408965", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398606.jpg", "positive_caption": ["There is exactly 1 plate."], "negative_caption": ["There are exactly 2 plates."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398606", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415752.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2415752", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357656.jpg", "positive_caption": ["There is exactly 1 scissor in the picture."], "negative_caption": ["There are exactly 0 scissors in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2357656", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338567.jpg", "positive_caption": ["There are exactly 2 ladies in the picture."], "negative_caption": ["There are exactly 0 ladies in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2338567", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393914.jpg", "positive_caption": ["There are exactly 3 people shown."], "negative_caption": ["There are exactly 2 people shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2393914", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384933.jpg", "positive_caption": ["There is exactly 1 girl in the photo."], "negative_caption": ["There are exactly 3 girls in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2384933", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330833.jpg", "positive_caption": ["There are exactly 2 tires on the motorcycle."], "negative_caption": ["There are exactly 3 tires on the motorcycle."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2330833", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407575.jpg", "positive_caption": ["There is exactly 1 bird pictured."], "negative_caption": ["There are exactly 2 birds pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2407575", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380228.jpg", "positive_caption": ["There is exactly 1 cat."], "negative_caption": ["There are exactly 2 cats."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2380228", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329334.jpg", "positive_caption": ["There is exactly 1 man."], "negative_caption": ["There are exactly 2 men."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2329334", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374489.jpg", "positive_caption": ["There is exactly 1 zebra."], "negative_caption": ["There are exactly 2 zebra."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2374489", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367527.jpg", "positive_caption": ["There is exactly 1 cake."], "negative_caption": ["There are exactly 2 cakes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367527", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354626.jpg", "positive_caption": ["There is exactly 1 man shown."], "negative_caption": ["There are exactly 2 men shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2354626", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390205.jpg", "positive_caption": ["There is exactly 1 person in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2390205", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348417.jpg", "positive_caption": ["There is exactly 1 palm tree."], "negative_caption": ["There are exactly 3 palm trees."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348417", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367703.jpg", "positive_caption": ["There is exactly 1 motorcycle."], "negative_caption": ["There are exactly 2 motorcycles."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367703", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336508.jpg", "positive_caption": ["There are exactly 2 am tracks in the picture."], "negative_caption": ["There is exactly 1 am track in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336508", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352202.jpg", "positive_caption": ["There are exactly 2 hands on the clock."], "negative_caption": ["There are exactly 3 hands on the clock."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2352202", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592568.jpg", "positive_caption": ["There are exactly 0 clouds."], "negative_caption": ["There are exactly 2 clouds."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592568", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415840.jpg", "positive_caption": ["There are exactly 2 elephants."], "negative_caption": ["There is exactly 1 elephant."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2415840", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713731.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713731", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416782.jpg", "positive_caption": ["Exactly 3 vases can be seen."], "negative_caption": ["Exactly 1 vase can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416782", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383866.jpg", "positive_caption": ["There are exactly 2 pieces of the sandwich."], "negative_caption": ["There is exactly 1 piece of the sandwich."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2383866", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371584.jpg", "positive_caption": ["There are exactly 2 wheels on the gate."], "negative_caption": ["There is exactly 1 wheel on the gate."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2371584", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341420.jpg", "positive_caption": ["There are exactly 2 articles of clothing hanging from the wall."], "negative_caption": ["There are exactly 0 articles of clothing hanging from the wall."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341420", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334168.jpg", "positive_caption": ["There is exactly 1 man on the snow."], "negative_caption": ["There are exactly 2 men on the snow."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334168", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413784.jpg", "positive_caption": ["There are exactly 2 flowers."], "negative_caption": ["There are exactly 3 flowers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413784", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403105.jpg", "positive_caption": ["There is exactly 1 donut."], "negative_caption": ["There are exactly 3 donuts."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2403105", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398945.jpg", "positive_caption": ["There is exactly 1 curtain shown."], "negative_caption": ["There are exactly 2 curtains shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398945", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368127.jpg", "positive_caption": ["There is exactly 1 horse in the picture."], "negative_caption": ["There are exactly 2 horses in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2368127", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342305.jpg", "positive_caption": ["There are exactly 3 players."], "negative_caption": ["There is exactly 1 player."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2342305", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395267.jpg", "positive_caption": ["There are exactly 2 stop lights."], "negative_caption": ["There are exactly 3 stop lights."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2395267", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374590.jpg", "positive_caption": ["There are exactly 3 garage doors present."], "negative_caption": ["There are exactly 2 garage doors present."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2374590", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402080.jpg", "positive_caption": ["There are exactly 2 people pictured."], "negative_caption": ["There are exactly 3 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2402080", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334896.jpg", "positive_caption": ["There are exactly 2 colors in the picture."], "negative_caption": ["There is exactly 1 color in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334896", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332988.jpg", "positive_caption": ["There is exactly 1 piece of meat in the bowl."], "negative_caption": ["There are exactly 0 pieces of meat in the bowl."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2332988", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345072.jpg", "positive_caption": ["There is exactly 1 elephant."], "negative_caption": ["There are exactly 3 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2345072", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364013.jpg", "positive_caption": ["There are exactly 3 people on the field."], "negative_caption": ["There are exactly 2 people on the field."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2364013", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397266.jpg", "positive_caption": ["There are exactly 2 boys wearing yellow."], "negative_caption": ["There are exactly 0 boys wearing yellow."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397266", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386486.jpg", "positive_caption": ["There is exactly 1 fork."], "negative_caption": ["There are exactly 0 forks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2386486", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370341.jpg", "positive_caption": ["There is exactly 1 teddy bear."], "negative_caption": ["There are exactly 2 teddy bears."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370341", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406996.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2406996", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414297.jpg", "positive_caption": ["There is exactly 1 bowl."], "negative_caption": ["There are exactly 3 bowls."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2414297", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390475.jpg", "positive_caption": ["There is exactly 1 person in focus."], "negative_caption": ["There are exactly 3 people in focus."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2390475", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325595.jpg", "positive_caption": ["There are exactly 3 people in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2325595", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391415.jpg", "positive_caption": ["There are exactly 0 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2391415", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397909.jpg", "positive_caption": ["There is exactly 1 horse."], "negative_caption": ["There are exactly 2 horses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397909", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339247.jpg", "positive_caption": ["There are exactly 3 light posts pictured."], "negative_caption": ["There are exactly 2 light posts pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339247", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403438.jpg", "positive_caption": ["There are exactly 2 headlights lit on the front of the train."], "negative_caption": ["There is exactly 1 headlight lit on the front of the train."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2403438", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367560.jpg", "positive_caption": ["There are exactly 2 cooks."], "negative_caption": ["There are exactly 3 cooks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367560", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334398.jpg", "positive_caption": ["There is exactly 1 dog."], "negative_caption": ["There are exactly 2 dogs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2334398", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361951.jpg", "positive_caption": ["There is exactly 1 train in this picture."], "negative_caption": ["There are exactly 3 trains in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2361951", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322204.jpg", "positive_caption": ["There is exactly 1 sandwich on the table."], "negative_caption": ["There are exactly 3 sandwiches on the table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2322204", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342025.jpg", "positive_caption": ["There are exactly 0 people in this photo."], "negative_caption": ["There are exactly 3 people in this photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2342025", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327674.jpg", "positive_caption": ["There are exactly 3 people in the room."], "negative_caption": ["There is exactly 1 person in the room."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327674", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340065.jpg", "positive_caption": ["There are exactly 2 snow goggles in the picture."], "negative_caption": ["There is exactly 1 snow goggle in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2340065", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360776.jpg", "positive_caption": ["There are exactly 3 people."], "negative_caption": ["There is exactly 1 person."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360776", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417103.jpg", "positive_caption": ["There are exactly 2 horses."], "negative_caption": ["There are exactly 3 horses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2417103", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319567.jpg", "positive_caption": ["There is exactly 1 marker in photo."], "negative_caption": ["There are exactly 3 markers in photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2319567", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319954.jpg", "positive_caption": ["There are exactly 3 giraffes."], "negative_caption": ["There are exactly 2 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2319954", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413776.jpg", "positive_caption": ["There are exactly 2 hoses in picture."], "negative_caption": ["There are exactly 3 hoses in picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413776", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365932.jpg", "positive_caption": ["There is exactly 1 person shown."], "negative_caption": ["There are exactly 3 people shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2365932", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367531.jpg", "positive_caption": ["There is exactly 1 tub."], "negative_caption": ["There are exactly 2 tubs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367531", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395930.jpg", "positive_caption": ["There are exactly 0 people shown."], "negative_caption": ["There is exactly 1 person shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2395930", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361120.jpg", "positive_caption": ["There is exactly 1 dishe."], "negative_caption": ["There are exactly 0 dishes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2361120", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376323.jpg", "positive_caption": ["There are exactly 2 bottles."], "negative_caption": ["There is exactly 1 bottle."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2376323", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397901.jpg", "positive_caption": ["There are exactly 2 computers."], "negative_caption": ["There is exactly 1 computer."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397901", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366811.jpg", "positive_caption": ["There are exactly 3 tables."], "negative_caption": ["There is exactly 1 table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2366811", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400812.jpg", "positive_caption": ["There are exactly 2 people people on the court."], "negative_caption": ["There is exactly 1 people person on the court."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2400812", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367721.jpg", "positive_caption": ["There are exactly 2 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2367721", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374587.jpg", "positive_caption": ["There are exactly 3 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2374587", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387104.jpg", "positive_caption": ["There are exactly 2 animals in this picture."], "negative_caption": ["There is exactly 1 animal in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2387104", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347007.jpg", "positive_caption": ["There is exactly 1 train."], "negative_caption": ["There are exactly 3 trains."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347007", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333627.jpg", "positive_caption": ["There are exactly 2 planes in the picture."], "negative_caption": ["There are exactly 3 planes in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2333627", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338501.jpg", "positive_caption": ["There are exactly 2 drinks."], "negative_caption": ["There are exactly 3 drinks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2338501", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346631.jpg", "positive_caption": ["There are exactly 2 dogs."], "negative_caption": ["There is exactly 1 dog."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2346631", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375812.jpg", "positive_caption": ["There is exactly 1 bus in the photo."], "negative_caption": ["There are exactly 3 buses in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2375812", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390844.jpg", "positive_caption": ["There is exactly 1 toilet."], "negative_caption": ["There are exactly 2 toilets."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2390844", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338820.jpg", "positive_caption": ["There is exactly 1 rug."], "negative_caption": ["There are exactly 2 rugs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2338820", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364534.jpg", "positive_caption": ["There are exactly 2 devices on."], "negative_caption": ["There is exactly 1 device on."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2364534", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354231.jpg", "positive_caption": ["There are exactly 3 people in the foreground."], "negative_caption": ["There are exactly 2 people in the foreground."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2354231", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413600.jpg", "positive_caption": ["There are exactly 0 chickens."], "negative_caption": ["There is exactly 1 chicken."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413600", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592096.jpg", "positive_caption": ["There are exactly 2 playing tennis."], "negative_caption": ["There are exactly 0 playing tenniss."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592096", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355743.jpg", "positive_caption": ["There is exactly 1 kite."], "negative_caption": ["There are exactly 2 kites."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2355743", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325932.jpg", "positive_caption": ["There is exactly 1 electric pole in the pictures."], "negative_caption": ["There are exactly 2 electric poles in the pictures."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2325932", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382534.jpg", "positive_caption": ["There are exactly 3 people."], "negative_caption": ["There are exactly 0 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2382534", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365836.jpg", "positive_caption": ["There is exactly 1 train shown."], "negative_caption": ["There are exactly 0 trains shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2365836", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381147.jpg", "positive_caption": ["There is exactly 1 red light in the photo."], "negative_caption": ["There are exactly 3 red lights in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381147", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417952.jpg", "positive_caption": ["There is exactly 1 sink."], "negative_caption": ["There are exactly 2 sinks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2417952", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412618.jpg", "positive_caption": ["There are exactly 2 giraffes."], "negative_caption": ["There is exactly 1 giraffe."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2412618", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376550.jpg", "positive_caption": ["There is exactly 1 person on a skateboard."], "negative_caption": ["There are exactly 3 people on a skateboard."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2376550", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347927.jpg", "positive_caption": ["There is exactly 1 hand sink."], "negative_caption": ["There are exactly 3 hand sinks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347927", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394783.jpg", "positive_caption": ["There are exactly 0 people in the kitchen."], "negative_caption": ["There is exactly 1 person in the kitchen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2394783", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366695.jpg", "positive_caption": ["There is exactly 1 train."], "negative_caption": ["There are exactly 3 trains."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2366695", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350487.jpg", "positive_caption": ["There is exactly 1 skier."], "negative_caption": ["There are exactly 0 skiers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2350487", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408858.jpg", "positive_caption": ["There are exactly 3 mushrooms."], "negative_caption": ["There are exactly 2 mushrooms."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2408858", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355279.jpg", "positive_caption": ["There is exactly 1 animal."], "negative_caption": ["There are exactly 3 animals."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2355279", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383672.jpg", "positive_caption": ["There are exactly 2 toilets."], "negative_caption": ["There are exactly 3 toilets."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2383672", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405059.jpg", "positive_caption": ["There is exactly 1 motorcycle in the picture."], "negative_caption": ["There are exactly 2 motorcycles in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2405059", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354675.jpg", "positive_caption": ["There are exactly 2 motorcycles."], "negative_caption": ["There is exactly 1 motorcycle."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2354675", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322243.jpg", "positive_caption": ["There are exactly 2 birds."], "negative_caption": ["There is exactly 1 bird."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2322243", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403097.jpg", "positive_caption": ["There are exactly 3 donuts being held up."], "negative_caption": ["There are exactly 2 donuts being held up."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2403097", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389858.jpg", "positive_caption": ["There is exactly 1 surfer."], "negative_caption": ["There are exactly 2 surfers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2389858", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362071.jpg", "positive_caption": ["There is exactly 1 car pictured."], "negative_caption": ["There are exactly 2 cars pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362071", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353988.jpg", "positive_caption": ["There are exactly 2 neckties."], "negative_caption": ["There is exactly 1 necktie."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2353988", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336991.jpg", "positive_caption": ["There are exactly 2 buildings the mopeds between."], "negative_caption": ["There is exactly 1 building the mopeds between."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336991", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408523.jpg", "positive_caption": ["There is exactly 1 bench."], "negative_caption": ["There are exactly 2 benches."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2408523", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388767.jpg", "positive_caption": ["There are exactly 0 clouds in the sky."], "negative_caption": ["There are exactly 3 clouds in the sky."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2388767", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351760.jpg", "positive_caption": ["There are exactly 3 seats."], "negative_caption": ["There are exactly 2 seats."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2351760", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396821.jpg", "positive_caption": ["There are exactly 2 people in the picture."], "negative_caption": ["There is exactly 1 person in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2396821", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348493.jpg", "positive_caption": ["There are exactly 2 cows."], "negative_caption": ["There are exactly 3 cows."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348493", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349109.jpg", "positive_caption": ["There is exactly 1 bird in this picture."], "negative_caption": ["There are exactly 0 birds in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2349109", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395678.jpg", "positive_caption": ["There are exactly 2 propellers."], "negative_caption": ["There are exactly 1 propellers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2395678", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150325.jpg", "positive_caption": ["There are exactly 3 balloons."], "negative_caption": ["There are exactly 2 balloons."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_150325", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398857.jpg", "positive_caption": ["Exactly 3 pieces of luggage can be seen."], "negative_caption": ["Exactly 1 piece of luggage can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398857", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347899.jpg", "positive_caption": ["There are exactly 2 pillows."], "negative_caption": ["There are exactly 3 pillows."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347899", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387114.jpg", "positive_caption": ["There are exactly 2 cows."], "negative_caption": ["There is exactly 1 cow."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2387114", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315439.jpg", "positive_caption": ["There are exactly 2 cups."], "negative_caption": ["There are exactly 3 cups."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2315439", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415299.jpg", "positive_caption": ["There are exactly 2 people in this image."], "negative_caption": ["There is exactly 1 person in this image."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2415299", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330437.jpg", "positive_caption": ["There is exactly 1 tv."], "negative_caption": ["There are exactly 3 tvs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2330437", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356726.jpg", "positive_caption": ["There are exactly 2 benches."], "negative_caption": ["There are exactly 0 benches."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2356726", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317571.jpg", "positive_caption": ["There is exactly 1 person in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2317571", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381964.jpg", "positive_caption": ["There are exactly 3 musicains in the photo."], "negative_caption": ["There are exactly 2 musicains in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381964", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343622.jpg", "positive_caption": ["There is exactly 1 animal pictured."], "negative_caption": ["There are exactly 2 animals pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2343622", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375379.jpg", "positive_caption": ["There are exactly 2 birds."], "negative_caption": ["There are exactly 3 birds."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2375379", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382726.jpg", "positive_caption": ["There is exactly 1 sign."], "negative_caption": ["There are exactly 2 signs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2382726", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335370.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There are exactly 3 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2335370", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397338.jpg", "positive_caption": ["There are exactly 0 people pictured."], "negative_caption": ["There are exactly 2 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397338", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403393.jpg", "positive_caption": ["There are exactly 2 zebras."], "negative_caption": ["There are exactly 3 zebras."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2403393", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366714.jpg", "positive_caption": ["Exactly 3 electrical wires can be seen here."], "negative_caption": ["Exactly 2 electrical wires can be seen here."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2366714", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385099.jpg", "positive_caption": ["There are exactly 3 faces in this picture."], "negative_caption": ["There are exactly 2 faces in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2385099", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323227.jpg", "positive_caption": ["There is exactly 1 man shown."], "negative_caption": ["There are exactly 3 men shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2323227", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404419.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2404419", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331106.jpg", "positive_caption": ["There are exactly 3 zebras shown."], "negative_caption": ["There is exactly 1 zebra shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2331106", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356492.jpg", "positive_caption": ["There are exactly 2 hamburgers in the photograph."], "negative_caption": ["There is exactly 1 hamburger in the photograph."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2356492", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397816.jpg", "positive_caption": ["There are exactly 3 planes visible."], "negative_caption": ["There is exactly 1 plane visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2397816", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414750.jpg", "positive_caption": ["There is exactly 1 plane."], "negative_caption": ["There are exactly 2 planes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2414750", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382601.jpg", "positive_caption": ["Exactly 2 ATVs can be seen."], "negative_caption": ["Exactly 1 ATV can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2382601", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403887.jpg", "positive_caption": ["There are exactly 2 colors on the train."], "negative_caption": ["There is exactly 1 color on the train."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2403887", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381980.jpg", "positive_caption": ["There is exactly 1 cruise ship."], "negative_caption": ["There are exactly 2 cruise ships."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381980", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159346.jpg", "positive_caption": ["There are exactly 3 pizzas in in front of the window."], "negative_caption": ["There are exactly 2 pizzas in in front of the window."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1159346", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370191.jpg", "positive_caption": ["There are exactly 0 women in this picture."], "negative_caption": ["There are exactly 2 women in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2370191", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340651.jpg", "positive_caption": ["There is exactly 1 tire pictured."], "negative_caption": ["There are exactly 3 tires pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2340651", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385692.jpg", "positive_caption": ["There are exactly 2 ladders on the side of the train."], "negative_caption": ["There are exactly 0 ladders on the side of the train."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2385692", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330441.jpg", "positive_caption": ["There are exactly 2 gloves pictured."], "negative_caption": ["There is exactly 1 glove pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2330441", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315640.jpg", "positive_caption": ["There is exactly 1 jet ski."], "negative_caption": ["There are exactly 2 jet skis."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2315640", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395280.jpg", "positive_caption": ["There is exactly 1 person in the water."], "negative_caption": ["There are exactly 2 people in the water."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2395280", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332058.jpg", "positive_caption": ["There are exactly 3 tracks shown."], "negative_caption": ["There is exactly 1 track shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2332058", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389813.jpg", "positive_caption": ["Not have a head dressing exactly 3 elephants."], "negative_caption": ["Not have a head dressing exactly 1 elephants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2389813", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353970.jpg", "positive_caption": ["There are exactly 2 clocks on the building."], "negative_caption": ["There is exactly 1 clock on the building."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2353970", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406909.jpg", "positive_caption": ["There are exactly 3 people shown."], "negative_caption": ["There is exactly 1 person shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2406909", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393768.jpg", "positive_caption": ["There are exactly 3 different views of the pizza."], "negative_caption": ["There is exactly 1 different view of the pizza."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2393768", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402784.jpg", "positive_caption": ["There is exactly 1 racket in the picture."], "negative_caption": ["There are exactly 2 rackets in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2402784", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347208.jpg", "positive_caption": ["There are exactly 2 pictures above the table."], "negative_caption": ["There is exactly 1 picture above the table."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347208", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336329.jpg", "positive_caption": ["There are exactly 2 elephants in the picture."], "negative_caption": ["There are exactly 3 elephants in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336329", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360860.jpg", "positive_caption": ["Exactly 2 planes can be seen."], "negative_caption": ["Exactly 1 plane can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360860", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319979.jpg", "positive_caption": ["There are exactly 2 elephants."], "negative_caption": ["There is exactly 1 elephant."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2319979", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393726.jpg", "positive_caption": ["There is exactly 1 table."], "negative_caption": ["There are exactly 3 tables."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2393726", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354468.jpg", "positive_caption": ["There are exactly 3 lights on the front of the train."], "negative_caption": ["There are exactly 2 lights on the front of the train."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2354468", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327986.jpg", "positive_caption": ["There are exactly 0 candles on the cake."], "negative_caption": ["There are exactly 3 candles on the cake."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2327986", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363425.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2363425", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386119.jpg", "positive_caption": ["There are exactly 2 clocks."], "negative_caption": ["There is exactly 1 clock."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2386119", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365956.jpg", "positive_caption": ["There are exactly 3 pendent lights showing."], "negative_caption": ["There are exactly 2 pendent lights showing."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2365956", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374842.jpg", "positive_caption": ["There are exactly 0 birds in the photo."], "negative_caption": ["There are exactly 2 birds in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2374842", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401053.jpg", "positive_caption": ["There is exactly 1 train."], "negative_caption": ["There are exactly 3 trains."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2401053", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325171.jpg", "positive_caption": ["There are exactly 0 people pictured here."], "negative_caption": ["There are exactly 2 people pictured here."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2325171", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339095.jpg", "positive_caption": ["There are exactly 2 tires on this vehicle."], "negative_caption": ["There are exactly 3 tires on this vehicle."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339095", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498124.jpg", "positive_caption": ["There are exactly 2 lights on the top , front of the train."], "negative_caption": ["There is exactly 1 light on the top , front of the train."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_498124", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592732.jpg", "positive_caption": ["There are exactly 0 people in the bleachers."], "negative_caption": ["There is exactly 1 person in the bleachers."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592732", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388062.jpg", "positive_caption": ["There are exactly 2 laptops in the photo."], "negative_caption": ["There is exactly 1 laptop in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2388062", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403474.jpg", "positive_caption": ["There are exactly 2 people."], "negative_caption": ["There are exactly 3 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2403474", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331486.jpg", "positive_caption": ["There are exactly 3 lights."], "negative_caption": ["There is exactly 1 light."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2331486", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353567.jpg", "positive_caption": ["There are exactly 2 giraffes."], "negative_caption": ["There are exactly 0 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2353567", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354053.jpg", "positive_caption": ["There is exactly 1 eye visible."], "negative_caption": ["There are exactly 3 eyes visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2354053", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338613.jpg", "positive_caption": ["There is exactly 1 skateboarder."], "negative_caption": ["There are exactly 3 skateboarders."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2338613", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412920.jpg", "positive_caption": ["There are exactly 2 lamps."], "negative_caption": ["There is exactly 1 lamp."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2412920", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380875.jpg", "positive_caption": ["There is exactly 1 plane pictured."], "negative_caption": ["There are exactly 2 planes pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2380875", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403049.jpg", "positive_caption": ["There are exactly 3 men."], "negative_caption": ["There is exactly 1 man."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2403049", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390916.jpg", "positive_caption": ["There are exactly 3 vehicles in the picture."], "negative_caption": ["There are exactly 1 vehicles in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2390916", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340913.jpg", "positive_caption": ["There are exactly 3 chairs."], "negative_caption": ["There are exactly 2 chairs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2340913", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376184.jpg", "positive_caption": ["There are exactly 2 clocks shown."], "negative_caption": ["There is exactly 1 clock shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2376184", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417650.jpg", "positive_caption": ["There is exactly 1 man in the water."], "negative_caption": ["There are exactly 3 men in the water."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2417650", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318127.jpg", "positive_caption": ["There are exactly 2 clocks visible."], "negative_caption": ["There is exactly 1 clock visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2318127", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362298.jpg", "positive_caption": ["There are exactly 2 lights on in the picture."], "negative_caption": ["There is exactly 1 light on in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362298", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320418.jpg", "positive_caption": ["There is exactly 1 umbrella."], "negative_caption": ["There are exactly 0 umbrellas."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320418", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385410.jpg", "positive_caption": ["There is exactly 1 surfer in the photo."], "negative_caption": ["There are exactly 3 surfers in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2385410", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400600.jpg", "positive_caption": ["There are exactly 2 people surfing."], "negative_caption": ["There are exactly 0 people surfing."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2400600", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344782.jpg", "positive_caption": ["There are exactly 2 pieces of cauliflower."], "negative_caption": ["There is exactly 1 piece of cauliflower."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2344782", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398044.jpg", "positive_caption": ["There are exactly 3 boats."], "negative_caption": ["There is exactly 1 boat."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398044", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392124.jpg", "positive_caption": ["There are exactly 2 zebras."], "negative_caption": ["There is exactly 1 zebra."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2392124", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399907.jpg", "positive_caption": ["There is exactly 1 person riding bikes."], "negative_caption": ["There are exactly 2 people riding bikes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2399907", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398143.jpg", "positive_caption": ["There are exactly 2 cars in the photo."], "negative_caption": ["There are exactly 0 cars in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398143", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363723.jpg", "positive_caption": ["There are exactly 2 lights on the sides of the bed."], "negative_caption": ["There is exactly 1 light on the sides of the bed."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2363723", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323814.jpg", "positive_caption": ["There is exactly 1 person."], "negative_caption": ["There are exactly 2 people."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2323814", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331701.jpg", "positive_caption": ["There are exactly 2 boys shown."], "negative_caption": ["There are exactly 3 boys shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2331701", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331050.jpg", "positive_caption": ["There are exactly 0 people pictured here."], "negative_caption": ["There is exactly 1 person pictured here."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2331050", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416400.jpg", "positive_caption": ["There are exactly 2 animals."], "negative_caption": ["There is exactly 1 animal."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416400", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360440.jpg", "positive_caption": ["There are exactly 3 bears."], "negative_caption": ["There are exactly 2 bears."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360440", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398367.jpg", "positive_caption": ["There is exactly 1 elephant in the image."], "negative_caption": ["There are exactly 3 elephants in the image."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2398367", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387441.jpg", "positive_caption": ["There are exactly 0 people in the picture."], "negative_caption": ["There are exactly 2 people in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2387441", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362000.jpg", "positive_caption": ["There is exactly 1 person in the photo."], "negative_caption": ["There are exactly 2 people in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2362000", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329745.jpg", "positive_caption": ["There are exactly 3 people in this image."], "negative_caption": ["There are exactly 0 people in this image."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2329745", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322426.jpg", "positive_caption": ["There is exactly 1 person pictured."], "negative_caption": ["There are exactly 2 people pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2322426", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359786.jpg", "positive_caption": ["There is exactly 1 bench."], "negative_caption": ["There are exactly 2 benches."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359786", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378740.jpg", "positive_caption": ["There are exactly 2 people in the ocean."], "negative_caption": ["There is exactly 1 person in the ocean."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2378740", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363629.jpg", "positive_caption": ["There are exactly 2 bears in the picture."], "negative_caption": ["There is exactly 1 bear in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2363629", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346323.jpg", "positive_caption": ["Exactly 1 horse trailer can be seen."], "negative_caption": ["Exactly 2 horse trailers can be seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2346323", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339074.jpg", "positive_caption": ["There are exactly 2 doors."], "negative_caption": ["There are exactly 3 doors."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339074", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392003.jpg", "positive_caption": ["There are exactly 2 green signs."], "negative_caption": ["There is exactly 1 green sign."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2392003", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324689.jpg", "positive_caption": ["There is exactly 1 woman shown."], "negative_caption": ["There are exactly 2 women shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2324689", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318497.jpg", "positive_caption": ["There is exactly 1 animal present."], "negative_caption": ["There are exactly 3 animals present."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2318497", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340760.jpg", "positive_caption": ["There are exactly 2 pillows on the couch."], "negative_caption": ["There are exactly 3 pillows on the couch."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2340760", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406328.jpg", "positive_caption": ["There is exactly 1 toilet in the bathroom."], "negative_caption": ["There are exactly 3 toilets in the bathroom."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2406328", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347055.jpg", "positive_caption": ["There are exactly 2 vases."], "negative_caption": ["There are exactly 0 vases."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2347055", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376215.jpg", "positive_caption": ["There are exactly 3 wheels on the bottom of the plane."], "negative_caption": ["There are exactly 2 wheels on the bottom of the plane."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2376215", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336735.jpg", "positive_caption": ["There are exactly 3 animals."], "negative_caption": ["There are exactly 2 animals."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336735", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333811.jpg", "positive_caption": ["There are exactly 3 palm trees."], "negative_caption": ["There is exactly 1 palm tree."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2333811", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713014.jpg", "positive_caption": ["There is exactly 1 traffic cone."], "negative_caption": ["There are exactly 2 traffic cones."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713014", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592996.jpg", "positive_caption": ["There are exactly 3 steps lead to the door."], "negative_caption": ["There are exactly 2 steps lead to the door."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592996", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359321.jpg", "positive_caption": ["There is exactly 1 microwave."], "negative_caption": ["There are exactly 0 microwaves."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2359321", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336770.jpg", "positive_caption": ["There are exactly 2 dishes."], "negative_caption": ["There is exactly 1 dish."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336770", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_286034.jpg", "positive_caption": ["There is exactly 1 truck."], "negative_caption": ["There are exactly 2 trucks."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_286034", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356683.jpg", "positive_caption": ["There are exactly 2 or the Cat's eyes visible."], "negative_caption": ["There is exactly 1 or the Cat's eyes visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2356683", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377400.jpg", "positive_caption": ["There are exactly 2 boats."], "negative_caption": ["There is exactly 1 boat."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2377400", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378037.jpg", "positive_caption": ["There is exactly 1 toilet."], "negative_caption": ["There are exactly 2 toilets."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2378037", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592601.jpg", "positive_caption": ["There are exactly 2 blue signs."], "negative_caption": ["There are exactly 0 blue signs."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_1592601", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335348.jpg", "positive_caption": ["There are exactly 2 buses."], "negative_caption": ["There are exactly 3 buses."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2335348", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713863.jpg", "positive_caption": ["The skateboarder has exactly 1 feel on the skateboard."], "negative_caption": ["The skateboarder has exactly 2 feels on the skateboard."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_713863", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345143.jpg", "positive_caption": ["There are exactly 3 gallons of orange drink."], "negative_caption": ["There is exactly 1 gallon of orange drink."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2345143", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391794.jpg", "positive_caption": ["There are exactly 2 people outside of the bus."], "negative_caption": ["There is exactly 1 person outside of the bus."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2391794", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339432.jpg", "positive_caption": ["There are exactly 3 people pictured."], "negative_caption": ["There is exactly 1 person pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2339432", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368810.jpg", "positive_caption": ["There are exactly 2 animals shown."], "negative_caption": ["There is exactly 1 animal shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2368810", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337766.jpg", "positive_caption": ["There are exactly 2 horses."], "negative_caption": ["There is exactly 1 horse."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2337766", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336014.jpg", "positive_caption": ["There are exactly 2 planes in the photo."], "negative_caption": ["There are exactly 0 planes in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2336014", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_497995.jpg", "positive_caption": ["There are exactly 2 players wear red shorts."], "negative_caption": ["There is exactly 1 player wear red shorts."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_497995", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394815.jpg", "positive_caption": ["There is exactly 1 giraffe."], "negative_caption": ["There are exactly 3 giraffes."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2394815", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400920.jpg", "positive_caption": ["There are exactly 0 dinosaurs in the picture."], "negative_caption": ["There are exactly 2 dinosaurs in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2400920", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348760.jpg", "positive_caption": ["There is exactly 1 person surfing."], "negative_caption": ["There are exactly 2 people surfing."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2348760", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375194.jpg", "positive_caption": ["There is exactly 1 gold poles."], "negative_caption": ["There are exactly 2 gold poles."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2375194", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396866.jpg", "positive_caption": ["There is exactly 1 chocolate drink in the tray."], "negative_caption": ["There are exactly 3 chocolate drinks in the tray."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2396866", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409105.jpg", "positive_caption": ["There is exactly 1 person skiing."], "negative_caption": ["There are exactly 2 people skiing."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2409105", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323154.jpg", "positive_caption": ["There are exactly 2 streets shown."], "negative_caption": ["There is exactly 1 street shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2323154", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381344.jpg", "positive_caption": ["There is exactly 1 fire hydrant."], "negative_caption": ["There are exactly 2 fire hydrants."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2381344", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393085.jpg", "positive_caption": ["There are exactly 3 animals in this picture."], "negative_caption": ["There is exactly 1 animal in this picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2393085", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340140.jpg", "positive_caption": ["There is exactly 1 trash can shown."], "negative_caption": ["There are exactly 2 trash cans shown."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2340140", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346677.jpg", "positive_caption": ["There is exactly 1 vehicle on the street."], "negative_caption": ["There are exactly 3 vehicles on the street."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2346677", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318439.jpg", "positive_caption": ["There are exactly 2 feet of the birds seen."], "negative_caption": ["There is exactly 1 foot of the birds seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2318439", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338233.jpg", "positive_caption": ["There are exactly 2 cows pictured."], "negative_caption": ["There is exactly 1 cow pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2338233", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411244.jpg", "positive_caption": ["There are exactly 2 still young."], "negative_caption": ["There is exactly 1 still young."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2411244", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320145.jpg", "positive_caption": ["There are exactly 2 planes."], "negative_caption": ["There is exactly 1 plane."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2320145", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403286.jpg", "positive_caption": ["There are exactly 0 people in the photo."], "negative_caption": ["There is exactly 1 person in the photo."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2403286", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390283.jpg", "positive_caption": ["There is exactly 1 tenni player visible."], "negative_caption": ["There are exactly 3 tennis players visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2390283", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360158.jpg", "positive_caption": ["There are exactly 2 arrows."], "negative_caption": ["There is exactly 1 arrow."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2360158", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2376385.jpg", "positive_caption": ["There are exactly 2 giraffes pictured."], "negative_caption": ["There is exactly 1 giraffe pictured."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2376385", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341318.jpg", "positive_caption": ["There is exactly 1 bus seen."], "negative_caption": ["There are exactly 2 buses seen."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2341318", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324150.jpg", "positive_caption": ["There are exactly 2 lamps visible."], "negative_caption": ["There are exactly 3 lamps visible."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2324150", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393086.jpg", "positive_caption": ["There are exactly 2 drumsticks."], "negative_caption": ["There is exactly 1 drumstick."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2393086", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416092.jpg", "positive_caption": ["There are exactly 2 women."], "negative_caption": ["There are exactly 3 women."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2416092", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413144.jpg", "positive_caption": ["There are exactly 2 trucks."], "negative_caption": ["There is exactly 1 truck."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2413144", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382502.jpg", "positive_caption": ["There is exactly 1 dog in the picture."], "negative_caption": ["There are exactly 2 dogs in the picture."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2382502", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387464.jpg", "positive_caption": ["There are exactly 2 players."], "negative_caption": ["There is exactly 1 player."], "original_file_name": "counting-small-quant", "dataset": "visual7w", "key": "counting_visual7w_2387464", "linguistic_phenomena": "counting", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371044.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371044", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393805.jpg", "positive_caption": ["There are no animals."], "negative_caption": ["There are animals."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2393805", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713025.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_713025", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316127.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2316127", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327531.jpg", "positive_caption": ["There are no birds pictured."], "negative_caption": ["There are birds pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2327531", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330133.jpg", "positive_caption": ["There are no dogs."], "negative_caption": ["There are dogs."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2330133", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338349.jpg", "positive_caption": ["There are no animals."], "negative_caption": ["There are animals."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2338349", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361154.jpg", "positive_caption": ["There are no pets pictured."], "negative_caption": ["There are pets pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361154", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363950.jpg", "positive_caption": ["no people's faces can you distinguish."], "negative_caption": ["People's faces can you distinguish."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363950", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367715.jpg", "positive_caption": ["There are no people shown."], "negative_caption": ["There are people shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367715", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370690.jpg", "positive_caption": ["There are no people pictured here."], "negative_caption": ["There are people pictured here."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370690", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373190.jpg", "positive_caption": ["There are no dogs in the picture."], "negative_caption": ["There are dogs in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2373190", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374842.jpg", "positive_caption": ["There are no birds in the photo."], "negative_caption": ["There are birds in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2374842", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592844.jpg", "positive_caption": ["There are no towels."], "negative_caption": ["There are towels."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1592844", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285805.jpg", "positive_caption": ["There are no clouds visible in the sky."], "negative_caption": ["There are clouds visible in the sky."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_285805", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285996.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_285996", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386509.jpg", "positive_caption": ["There are no animals in this picture."], "negative_caption": ["There are animals in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2386509", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387946.jpg", "positive_caption": ["There are no animals."], "negative_caption": ["There are animals."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2387946", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390727.jpg", "positive_caption": ["There are no animals."], "negative_caption": ["There are animals."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2390727", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401869.jpg", "positive_caption": ["There are no people visible."], "negative_caption": ["There are people visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2401869", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409603.jpg", "positive_caption": ["There are no dogs on the beach."], "negative_caption": ["There are dogs on the beach."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2409603", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414337.jpg", "positive_caption": ["There are no lamps on the table."], "negative_caption": ["There are lamps on the table."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2414337", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316052.jpg", "positive_caption": ["There are no children in the photo."], "negative_caption": ["There are children in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2316052", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323408.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2323408", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325117.jpg", "positive_caption": ["There are no humans touching the bird."], "negative_caption": ["There are humans touching the bird."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2325117", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325587.jpg", "positive_caption": ["There are no people visible."], "negative_caption": ["There are people visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2325587", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327986.jpg", "positive_caption": ["There are no candles on the cake."], "negative_caption": ["There are candles on the cake."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2327986", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330023.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2330023", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336798.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2336798", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339987.jpg", "positive_caption": ["There are no animals in this picture."], "negative_caption": ["There are animals in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2339987", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349860.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2349860", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352298.jpg", "positive_caption": ["There are no clouds in the sky."], "negative_caption": ["There are clouds in the sky."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2352298", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356111.jpg", "positive_caption": ["There are no animals."], "negative_caption": ["There are animals."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2356111", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359425.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2359425", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359468.jpg", "positive_caption": ["There are no clowns in the photo."], "negative_caption": ["There are clowns in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2359468", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359865.jpg", "positive_caption": ["There are no people on the track."], "negative_caption": ["There are people on the track."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2359865", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359966.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2359966", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360156.jpg", "positive_caption": ["There are no people shown."], "negative_caption": ["There are people shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2360156", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360779.jpg", "positive_caption": ["There are no people in this photo."], "negative_caption": ["There are people in this photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2360779", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361996.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361996", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362983.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362983", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364010.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2364010", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365038.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2365038", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367076.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367076", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368190.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2368190", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370191.jpg", "positive_caption": ["There are no women in this picture."], "negative_caption": ["There are women in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370191", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285848.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_285848", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370812.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370812", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371111.jpg", "positive_caption": ["There are no animals in this picture."], "negative_caption": ["There are animals in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371111", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371493.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371493", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371597.jpg", "positive_caption": ["There are no cars."], "negative_caption": ["There are cars."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371597", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372230.jpg", "positive_caption": ["There are no people visible."], "negative_caption": ["There are people visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2372230", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372572.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2372572", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372870.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2372870", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373047.jpg", "positive_caption": ["There are no animals."], "negative_caption": ["There are animals."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2373047", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373121.jpg", "positive_caption": ["There are no clouds in the sky."], "negative_caption": ["There are clouds in the sky."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2373121", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373591.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2373591", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373845.jpg", "positive_caption": ["There are no people visible."], "negative_caption": ["There are people visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2373845", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373889.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2373889", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374237.jpg", "positive_caption": ["There are no people riding the horses."], "negative_caption": ["There are people riding the horses."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2374237", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374547.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2374547", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2374559.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2374559", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375916.jpg", "positive_caption": ["There are no people riding the motorcycle."], "negative_caption": ["There are people riding the motorcycle."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2375916", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592049.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1592049", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378568.jpg", "positive_caption": ["There are no people pictured here."], "negative_caption": ["There are people pictured here."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2378568", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150392.jpg", "positive_caption": ["There are no clouds in sight."], "negative_caption": ["There are clouds in sight."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_150392", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592500.jpg", "positive_caption": ["There are no people here."], "negative_caption": ["There are people here."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1592500", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592568.jpg", "positive_caption": ["There are no clouds."], "negative_caption": ["There are clouds."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1592568", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592732.jpg", "positive_caption": ["There are no people in the bleachers."], "negative_caption": ["There are people in the bleachers."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1592732", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379274.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2379274", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1593022.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1593022", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380468.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2380468", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381149.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2381149", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382591.jpg", "positive_caption": ["There are no dogs visible."], "negative_caption": ["There are dogs visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2382591", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285923.jpg", "positive_caption": ["There are no trains on the tracks."], "negative_caption": ["There are trains on the tracks."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_285923", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285977.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_285977", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383309.jpg", "positive_caption": ["There are no people in the tub."], "negative_caption": ["There are people in the tub."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2383309", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383311.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2383311", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383458.jpg", "positive_caption": ["There are no people in the image."], "negative_caption": ["There are people in the image."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2383458", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2383699.jpg", "positive_caption": ["There are no people visible."], "negative_caption": ["There are people visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2383699", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2384553.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2384553", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385384.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2385384", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385711.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2385711", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386201.jpg", "positive_caption": ["There are no cars on the baseball field."], "negative_caption": ["There are cars on the baseball field."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2386201", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387013.jpg", "positive_caption": ["There are no people in picture."], "negative_caption": ["There are people in picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2387013", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387440.jpg", "positive_caption": ["There are no humans in the picture."], "negative_caption": ["There are humans in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2387440", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2387441.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2387441", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388767.jpg", "positive_caption": ["There are no clouds in the sky."], "negative_caption": ["There are clouds in the sky."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2388767", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389326.jpg", "positive_caption": ["There are no animals."], "negative_caption": ["There are animals."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2389326", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390402.jpg", "positive_caption": ["no pieces have been taken from the pizza."], "negative_caption": ["Pieces have been taken from the pizza."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2390402", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390850.jpg", "positive_caption": ["There are no people in the water."], "negative_caption": ["There are people in the water."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2390850", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2390942.jpg", "positive_caption": ["You see no people ."], "negative_caption": ["You see people ."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2390942", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391215.jpg", "positive_caption": ["There are no people in picture."], "negative_caption": ["There are people in picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2391215", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391415.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2391415", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391766.jpg", "positive_caption": ["There are no birds in the sky."], "negative_caption": ["There are birds in the sky."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2391766", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392312.jpg", "positive_caption": ["There are no people in the bathroom."], "negative_caption": ["There are people in the bathroom."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2392312", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392555.jpg", "positive_caption": ["There are no animals in the picture."], "negative_caption": ["There are animals in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2392555", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392973.jpg", "positive_caption": ["There are no people seen."], "negative_caption": ["There are people seen."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2392973", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393679.jpg", "positive_caption": ["There are no animals shown."], "negative_caption": ["There are animals shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2393679", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393859.jpg", "positive_caption": ["There are no people in the room."], "negative_caption": ["There are people in the room."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2393859", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393889.jpg", "positive_caption": ["There are no people crossing the street."], "negative_caption": ["There are people crossing the street."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2393889", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394051.jpg", "positive_caption": ["There are no women."], "negative_caption": ["There are women."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2394051", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394310.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2394310", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394557.jpg", "positive_caption": ["There are no people in this photo."], "negative_caption": ["There are people in this photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2394557", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394783.jpg", "positive_caption": ["There are no people in the kitchen."], "negative_caption": ["There are people in the kitchen."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2394783", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395077.jpg", "positive_caption": ["There are no animals in the photo."], "negative_caption": ["There are animals in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2395077", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2395930.jpg", "positive_caption": ["There are no people shown."], "negative_caption": ["There are people shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2395930", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396309.jpg", "positive_caption": ["There are no planes shown."], "negative_caption": ["There are planes shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2396309", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396386.jpg", "positive_caption": ["There are no elephants pictured."], "negative_caption": ["There are elephants pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2396386", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2396743.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2396743", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397031.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2397031", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397338.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2397338", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398412.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2398412", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400052.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2400052", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400365.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2400365", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400644.jpg", "positive_caption": ["There are no children."], "negative_caption": ["There are children."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2400644", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400879.jpg", "positive_caption": ["There are no horses."], "negative_caption": ["There are horses."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2400879", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400920.jpg", "positive_caption": ["There are no dinosaurs in the picture."], "negative_caption": ["There are dinosaurs in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2400920", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400921.jpg", "positive_caption": ["There are no dinosaurs in the picture."], "negative_caption": ["There are dinosaurs in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2400921", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401170.jpg", "positive_caption": ["There are no cars shown."], "negative_caption": ["There are cars shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2401170", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401288.jpg", "positive_caption": ["There are no people pictured here."], "negative_caption": ["There are people pictured here."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2401288", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401627.jpg", "positive_caption": ["There are no people paying to attention to the guy in the air."], "negative_caption": ["There are people paying to attention to the guy in the air."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2401627", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401699.jpg", "positive_caption": ["There are no windows in the building."], "negative_caption": ["There are windows in the building."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2401699", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402072.jpg", "positive_caption": ["There are no people in this picture."], "negative_caption": ["There are people in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2402072", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402139.jpg", "positive_caption": ["There are no clouds in the sky."], "negative_caption": ["There are clouds in the sky."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2402139", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402788.jpg", "positive_caption": ["There are no people in picture."], "negative_caption": ["There are people in picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2402788", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403149.jpg", "positive_caption": ["There are no people pictured here."], "negative_caption": ["There are people pictured here."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2403149", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403284.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2403284", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403286.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2403286", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403870.jpg", "positive_caption": ["There are no people shown."], "negative_caption": ["There are people shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2403870", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404069.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2404069", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404185.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2404185", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404802.jpg", "positive_caption": ["There are no people shown."], "negative_caption": ["There are people shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2404802", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405052.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2405052", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405117.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2405117", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406500.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2406500", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406729.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2406729", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406837.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2406837", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406996.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2406996", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411229.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2411229", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411632.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2411632", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411827.jpg", "positive_caption": ["There are no people visible."], "negative_caption": ["There are people visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2411827", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412162.jpg", "positive_caption": ["You see no people in the bus."], "negative_caption": ["You see people in the bus."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2412162", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412168.jpg", "positive_caption": ["There are no windows in the photo."], "negative_caption": ["There are windows in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2412168", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413132.jpg", "positive_caption": ["There are no people in this picture."], "negative_caption": ["There are people in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2413132", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413486.jpg", "positive_caption": ["There are no people wearing a helmet."], "negative_caption": ["There are people wearing a helmet."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2413486", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413592.jpg", "positive_caption": ["There are no of his feet touching the ground."], "negative_caption": ["There are of his feet touching the ground."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2413592", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2413600.jpg", "positive_caption": ["There are no chickens."], "negative_caption": ["There are chickens."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2413600", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_150258.jpg", "positive_caption": ["There are no buildings in the photo."], "negative_caption": ["There are buildings in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_150258", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415439.jpg", "positive_caption": ["There are no elephants pictured."], "negative_caption": ["There are elephants pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2415439", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415752.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2415752", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416008.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2416008", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416634.jpg", "positive_caption": ["There are no dolphins visible."], "negative_caption": ["There are dolphins visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2416634", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416837.jpg", "positive_caption": ["There are no dinosaurs in the picture."], "negative_caption": ["There are dinosaurs in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2416837", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713666.jpg", "positive_caption": ["There are no people on the bus."], "negative_caption": ["There are people on the bus."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_713666", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713731.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_713731", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_61601.jpg", "positive_caption": ["There are no clouds in the sky."], "negative_caption": ["There are clouds in the sky."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_61601", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316044.jpg", "positive_caption": ["There are no people riding on elephants."], "negative_caption": ["There are people riding on elephants."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2316044", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316045.jpg", "positive_caption": ["There are no elephants pictured."], "negative_caption": ["There are elephants pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2316045", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316446.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2316446", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316568.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2316568", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316793.jpg", "positive_caption": ["There are no people pictured here."], "negative_caption": ["There are people pictured here."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2316793", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317102.jpg", "positive_caption": ["There are no dogs."], "negative_caption": ["There are dogs."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2317102", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317862.jpg", "positive_caption": ["There are no people riding on elephants."], "negative_caption": ["There are people riding on elephants."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2317862", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318181.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2318181", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318981.jpg", "positive_caption": ["There are no giraffes."], "negative_caption": ["There are giraffes."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2318981", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319138.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2319138", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319653.jpg", "positive_caption": ["There are no people riding on elephants."], "negative_caption": ["There are people riding on elephants."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2319653", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319795.jpg", "positive_caption": ["There are no people riding on elephants."], "negative_caption": ["There are people riding on elephants."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2319795", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320525.jpg", "positive_caption": ["There are no pets shown."], "negative_caption": ["There are pets shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2320525", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2321705.jpg", "positive_caption": ["There are no dinosaurs in this picture."], "negative_caption": ["There are dinosaurs in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2321705", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322440.jpg", "positive_caption": ["There are no animals seen."], "negative_caption": ["There are animals seen."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2322440", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2322780.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2322780", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323364.jpg", "positive_caption": ["There are no cats."], "negative_caption": ["There are cats."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2323364", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323684.jpg", "positive_caption": ["There are no rolls of toilet paper."], "negative_caption": ["There are rolls of toilet paper."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2323684", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323944.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2323944", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325171.jpg", "positive_caption": ["There are no people pictured here."], "negative_caption": ["There are people pictured here."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2325171", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325309.jpg", "positive_caption": ["There are no animals pictured."], "negative_caption": ["There are animals pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2325309", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325708.jpg", "positive_caption": ["There are no dogs in the room."], "negative_caption": ["There are dogs in the room."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2325708", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326282.jpg", "positive_caption": ["There are no people sitting on the sofa."], "negative_caption": ["There are people sitting on the sofa."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2326282", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326561.jpg", "positive_caption": ["There are no deer on the tracks."], "negative_caption": ["There are deer on the tracks."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2326561", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327005.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2327005", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327010.jpg", "positive_caption": ["There are no people in the scene."], "negative_caption": ["There are people in the scene."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2327010", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327499.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2327499", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327568.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2327568", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2327763.jpg", "positive_caption": ["There are no people visible."], "negative_caption": ["There are people visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2327763", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328265.jpg", "positive_caption": ["There are no ducks."], "negative_caption": ["There are ducks."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2328265", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328270.jpg", "positive_caption": ["There are no people in the image."], "negative_caption": ["There are people in the image."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2328270", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328544.jpg", "positive_caption": ["There are no birds in the sky."], "negative_caption": ["There are birds in the sky."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2328544", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328887.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2328887", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329511.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2329511", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2329660.jpg", "positive_caption": ["There are no animals in the photo."], "negative_caption": ["There are animals in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2329660", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330185.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2330185", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2330611.jpg", "positive_caption": ["There are no dogs."], "negative_caption": ["There are dogs."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2330611", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331050.jpg", "positive_caption": ["There are no people pictured here."], "negative_caption": ["There are people pictured here."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2331050", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331342.jpg", "positive_caption": ["There are no people in this picture."], "negative_caption": ["There are people in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2331342", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331664.jpg", "positive_caption": ["There are no people in this image."], "negative_caption": ["There are people in this image."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2331664", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333282.jpg", "positive_caption": ["There are no people in the window."], "negative_caption": ["There are people in the window."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2333282", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334324.jpg", "positive_caption": ["There are no stars."], "negative_caption": ["There are stars."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2334324", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334562.jpg", "positive_caption": ["There are no boats."], "negative_caption": ["There are boats."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2334562", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2335370.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2335370", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336008.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2336008", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2336172.jpg", "positive_caption": ["There are no animals pictured."], "negative_caption": ["There are animals pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2336172", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337387.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2337387", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2337483.jpg", "positive_caption": ["There are no people on the platform."], "negative_caption": ["There are people on the platform."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2337483", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338045.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2338045", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338061.jpg", "positive_caption": ["There are no people shown."], "negative_caption": ["There are people shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2338061", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339031.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2339031", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159467.jpg", "positive_caption": ["There are no cars visible in the street."], "negative_caption": ["There are cars visible in the street."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1159467", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339428.jpg", "positive_caption": ["There are no elephants pictured."], "negative_caption": ["There are elephants pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2339428", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339624.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2339624", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340427.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2340427", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340642.jpg", "positive_caption": ["There are no women in the image."], "negative_caption": ["There are women in the image."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2340642", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340899.jpg", "positive_caption": ["There are no people in the image."], "negative_caption": ["There are people in the image."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2340899", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341114.jpg", "positive_caption": ["There are no dogs in the photo."], "negative_caption": ["There are dogs in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2341114", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341644.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2341644", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341686.jpg", "positive_caption": ["There are no people sitting on the couch."], "negative_caption": ["There are people sitting on the couch."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2341686", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2341809.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2341809", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342025.jpg", "positive_caption": ["There are no people in this photo."], "negative_caption": ["There are people in this photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2342025", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378335.jpg", "positive_caption": ["There are no chairs in the room."], "negative_caption": ["There are chairs in the room."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2378335", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342550.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2342550", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342903.jpg", "positive_caption": ["There are no clipboards sitting on the bed."], "negative_caption": ["There are clipboards sitting on the bed."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2342903", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343236.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2343236", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343427.jpg", "positive_caption": ["no people can be seen."], "negative_caption": ["People can be seen."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2343427", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334867.jpg", "positive_caption": ["There are no dinosaurs in the picture."], "negative_caption": ["There are dinosaurs in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2334867", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344761.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2344761", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345066.jpg", "positive_caption": ["There are no birds in the sky."], "negative_caption": ["There are birds in the sky."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2345066", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345780.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2345780", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345801.jpg", "positive_caption": ["There are no animals."], "negative_caption": ["There are animals."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2345801", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346245.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2346245", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346324.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2346324", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346733.jpg", "positive_caption": ["There are no people in the shot."], "negative_caption": ["There are people in the shot."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2346733", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348569.jpg", "positive_caption": ["There are no animals shown."], "negative_caption": ["There are animals shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2348569", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349512.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2349512", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2349587.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2349587", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351326.jpg", "positive_caption": ["There are no animals appear in this picture."], "negative_caption": ["There are animals appear in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2351326", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351464.jpg", "positive_caption": ["There are no pets."], "negative_caption": ["There are pets."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2351464", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353629.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2353629", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353960.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2353960", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354145.jpg", "positive_caption": ["There are no closed suitcases."], "negative_caption": ["There are closed suitcases."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2354145", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354159.jpg", "positive_caption": ["There are no people riding the bikes."], "negative_caption": ["There are people riding the bikes."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2354159", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354742.jpg", "positive_caption": ["no slices of pizza have been eaten."], "negative_caption": ["Slices of pizza have been eaten."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2354742", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2354789.jpg", "positive_caption": ["There are no horses in the picture."], "negative_caption": ["There are horses in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2354789", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355640.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2355640", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2355887.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2355887", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356523.jpg", "positive_caption": ["There are no animals in the picture."], "negative_caption": ["There are animals in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2356523", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356753.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2356753", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356908.jpg", "positive_caption": ["There are no people feeding the cow."], "negative_caption": ["There are people feeding the cow."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2356908", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357109.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2357109", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357139.jpg", "positive_caption": ["There are no people."], "negative_caption": ["There are people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2357139", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357944.jpg", "positive_caption": ["There are no people pictured."], "negative_caption": ["There are people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2357944", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358152.jpg", "positive_caption": ["There are no people in the picture."], "negative_caption": ["There are people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2358152", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358663.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2358663", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358694.jpg", "positive_caption": ["There are no people shown."], "negative_caption": ["There are people shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2358694", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2358835.jpg", "positive_caption": ["There are no people in the photo."], "negative_caption": ["There are people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2358835", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359029.jpg", "positive_caption": ["There are no animals."], "negative_caption": ["There are animals."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2359029", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1.jpg", "positive_caption": ["There are cars parked."], "negative_caption": ["There are no cars parked."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360434.jpg", "positive_caption": ["There are signs pictured."], "negative_caption": ["There are no signs pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2360434", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360933.jpg", "positive_caption": ["There are floor grates visible."], "negative_caption": ["There are no floor grates visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2360933", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361244.jpg", "positive_caption": ["There are zebras in photo."], "negative_caption": ["There are no zebras in photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361244", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361437.jpg", "positive_caption": ["There are cows shown."], "negative_caption": ["There are no cows shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361437", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362471.jpg", "positive_caption": ["The elephants have tusks."], "negative_caption": ["The elephants have no tusks."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362471", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362476.jpg", "positive_caption": ["There are eagles visible."], "negative_caption": ["There are no eagles visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362476", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362752.jpg", "positive_caption": ["There are skateboarders."], "negative_caption": ["There are no skateboarders."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362752", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363712.jpg", "positive_caption": ["You see horses in the image."], "negative_caption": ["You see no horses in the image."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363712", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363965.jpg", "positive_caption": ["ford logos can be seen."], "negative_caption": ["No ford logos can be seen."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363965", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363971.jpg", "positive_caption": ["There are people in the photo."], "negative_caption": ["There are no people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363971", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364922.jpg", "positive_caption": ["There are pizzas."], "negative_caption": ["There are no pizzas."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2364922", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365208.jpg", "positive_caption": ["There are people on the elephants."], "negative_caption": ["There are no people on the elephants."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2365208", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365548.jpg", "positive_caption": ["There are people pictured."], "negative_caption": ["There are no people pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2365548", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366034.jpg", "positive_caption": ["There are pillows."], "negative_caption": ["There are no pillows."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2366034", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366163.jpg", "positive_caption": ["There are windows visible."], "negative_caption": ["There are no windows visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2366163", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366253.jpg", "positive_caption": ["There are people in the photo."], "negative_caption": ["There are no people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2366253", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367490.jpg", "positive_caption": ["There are motorcycles."], "negative_caption": ["There are no motorcycles."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367490", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367942.jpg", "positive_caption": ["There are propellers on the plane."], "negative_caption": ["There are no propellers on the plane."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367942", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368143.jpg", "positive_caption": ["bottles have blue caps."], "negative_caption": ["No bottles have blue caps."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2368143", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369128.jpg", "positive_caption": ["There are zebras."], "negative_caption": ["There are no zebras."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2369128", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369658.jpg", "positive_caption": ["There are toys on the bed."], "negative_caption": ["There are no toys on the bed."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2369658", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370873.jpg", "positive_caption": ["There are plates shown in the photo."], "negative_caption": ["There are no plates shown in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370873", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372073.jpg", "positive_caption": ["There are people in the picture."], "negative_caption": ["There are no people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2372073", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372473.jpg", "positive_caption": ["There are scooters in the photo."], "negative_caption": ["There are no scooters in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2372473", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372620.jpg", "positive_caption": ["There are kites flying."], "negative_caption": ["There are no kites flying."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2372620", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372701.jpg", "positive_caption": ["There are legs visible."], "negative_caption": ["There are no legs visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2372701", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2372786.jpg", "positive_caption": ["There are plates shown."], "negative_caption": ["There are no plates shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2372786", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373128.jpg", "positive_caption": ["There are pieces of food on the plate."], "negative_caption": ["There are no pieces of food on the plate."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2373128", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2373565.jpg", "positive_caption": ["There are men in the scene."], "negative_caption": ["There are no men in the scene."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2373565", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375454.jpg", "positive_caption": ["There are dishes in the picture."], "negative_caption": ["There are no dishes in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2375454", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2375837.jpg", "positive_caption": ["There are writing utensils clearly visible."], "negative_caption": ["There are no writing utensils clearly visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2375837", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2377797.jpg", "positive_caption": ["There is a black horses in the scene."], "negative_caption": ["There is no black horses in the scene."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2377797", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378084.jpg", "positive_caption": ["There are elephants."], "negative_caption": ["There are no elephants."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2378084", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1591818.jpg", "positive_caption": ["There are bicycles."], "negative_caption": ["There are no bicycles."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1591818", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592315.jpg", "positive_caption": ["There are green bunches of bananas."], "negative_caption": ["There are no green bunches of bananas."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1592315", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378887.jpg", "positive_caption": ["There are men playing."], "negative_caption": ["There are no men playing."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2378887", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592557.jpg", "positive_caption": ["There are cones."], "negative_caption": ["There are no cones."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1592557", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379053.jpg", "positive_caption": ["There are people visible."], "negative_caption": ["There are no people visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2379053", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1592835.jpg", "positive_caption": ["There are chairs."], "negative_caption": ["There are no chairs."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1592835", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379433.jpg", "positive_caption": ["There are wheels on the skateboard."], "negative_caption": ["There are no wheels on the skateboard."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2379433", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379573.jpg", "positive_caption": ["There are train tracks."], "negative_caption": ["There are no train tracks."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2379573", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380321.jpg", "positive_caption": ["There are pieces of carrots in the picture."], "negative_caption": ["There are no pieces of carrots in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2380321", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2380782.jpg", "positive_caption": ["There are horses."], "negative_caption": ["There are no horses."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2380782", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381178.jpg", "positive_caption": ["There are signs on the post."], "negative_caption": ["There are no signs on the post."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2381178", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2381725.jpg", "positive_caption": ["There is a doughnut in the picture."], "negative_caption": ["There is no doughnut in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2381725", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2382639.jpg", "positive_caption": ["There are pots on the top shelf."], "negative_caption": ["There are no pots on the top shelf."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2382639", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_285933.jpg", "positive_caption": ["There are blueberries."], "negative_caption": ["There are no blueberries."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_285933", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_286034.jpg", "positive_caption": ["There is a truck."], "negative_caption": ["There is no truck."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_286034", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385099.jpg", "positive_caption": ["There are faces in this picture."], "negative_caption": ["There are no faces in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2385099", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2385149.jpg", "positive_caption": ["There are pillows stacked."], "negative_caption": ["There are no pillows stacked."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2385149", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2386605.jpg", "positive_caption": ["people can be seen on the bus."], "negative_caption": ["No people can be seen on the bus."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2386605", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2388051.jpg", "positive_caption": ["There are people."], "negative_caption": ["There are no people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2388051", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2389519.jpg", "positive_caption": ["There are bikes on the rack."], "negative_caption": ["There are no bikes on the rack."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2389519", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391208.jpg", "positive_caption": ["There are zebras in the picture."], "negative_caption": ["There are no zebras in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2391208", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2391321.jpg", "positive_caption": ["There are cows."], "negative_caption": ["There are no cows."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2391321", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392387.jpg", "positive_caption": ["There are bears."], "negative_caption": ["There are no bears."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2392387", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392482.jpg", "positive_caption": ["There are planes in the background."], "negative_caption": ["There are no planes in the background."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2392482", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2392484.jpg", "positive_caption": ["There are shoes shown."], "negative_caption": ["There are no shoes shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2392484", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393243.jpg", "positive_caption": ["There are birds."], "negative_caption": ["There are no birds."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2393243", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393355.jpg", "positive_caption": ["There are players or shown."], "negative_caption": ["There are no players or shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2393355", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393653.jpg", "positive_caption": ["There are colors in the girl's shirt."], "negative_caption": ["There are no colors in the girl's shirt."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2393653", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2393836.jpg", "positive_caption": ["There are tires on the car."], "negative_caption": ["There are no tires on the car."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2393836", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2394602.jpg", "positive_caption": ["There are women in the picture."], "negative_caption": ["There are no women in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2394602", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2397608.jpg", "positive_caption": ["There are vases shown."], "negative_caption": ["There are no vases shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2397608", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398382.jpg", "positive_caption": ["There are zebras."], "negative_caption": ["There are no zebras."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2398382", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398455.jpg", "positive_caption": ["There are players."], "negative_caption": ["There are no players."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2398455", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2398674.jpg", "positive_caption": ["There are kids in the pic."], "negative_caption": ["There are no kids in the pic."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2398674", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399357.jpg", "positive_caption": ["There are giraffe."], "negative_caption": ["There are no giraffe."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2399357", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2399922.jpg", "positive_caption": ["There are people in the water."], "negative_caption": ["There are no people in the water."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2399922", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2400857.jpg", "positive_caption": ["There are people in the picture."], "negative_caption": ["There are no people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2400857", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401335.jpg", "positive_caption": ["There are wall sconces visible in this picture."], "negative_caption": ["There are no wall sconces visible in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2401335", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401445.jpg", "positive_caption": ["There are surfboards shown."], "negative_caption": ["There are no surfboards shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2401445", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401904.jpg", "positive_caption": ["There is a green buildings in the picture."], "negative_caption": ["There is no green buildings in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2401904", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2401974.jpg", "positive_caption": ["There are chimneys."], "negative_caption": ["There are no chimneys."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2401974", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2402074.jpg", "positive_caption": ["There are red vehicles."], "negative_caption": ["There are no red vehicles."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2402074", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2403793.jpg", "positive_caption": ["There are wheels on the skateboard."], "negative_caption": ["There are no wheels on the skateboard."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2403793", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344871.jpg", "positive_caption": ["There are people shown."], "negative_caption": ["There are no people shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2344871", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2404317.jpg", "positive_caption": ["There are planes in the photo."], "negative_caption": ["There are no planes in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2404317", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2405440.jpg", "positive_caption": ["There are people in the photo."], "negative_caption": ["There are no people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2405440", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406033.jpg", "positive_caption": ["There is a suit."], "negative_caption": ["There is no suit."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2406033", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2406684.jpg", "positive_caption": ["There is a lamp."], "negative_caption": ["There is no lamp."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2406684", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2407816.jpg", "positive_caption": ["There are power lines."], "negative_caption": ["There are no power lines."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2407816", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408431.jpg", "positive_caption": ["There are strings on the kite."], "negative_caption": ["There are no strings on the kite."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2408431", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2408510.jpg", "positive_caption": ["There are dials on the microwave."], "negative_caption": ["There are no dials on the microwave."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2408510", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409553.jpg", "positive_caption": ["There is a flower."], "negative_caption": ["There is no flower."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2409553", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409635.jpg", "positive_caption": ["There are trees in the forefront of the picture."], "negative_caption": ["There are no trees in the forefront of the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2409635", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2409813.jpg", "positive_caption": ["There are round glass containers."], "negative_caption": ["There are no round glass containers."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2409813", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410005.jpg", "positive_caption": ["There are men on each team."], "negative_caption": ["There are no men on each team."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2410005", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2410671.jpg", "positive_caption": ["There are giraffes."], "negative_caption": ["There are no giraffes."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2410671", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411479.jpg", "positive_caption": ["There are doughnuts appear to be yellow."], "negative_caption": ["There are no doughnuts appear to be yellow."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2411479", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2411942.jpg", "positive_caption": ["There are zebras in the picture."], "negative_caption": ["There are no zebras in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2411942", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2412169.jpg", "positive_caption": ["There are windows visible on the building."], "negative_caption": ["There are no windows visible on the building."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2412169", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414848.jpg", "positive_caption": ["There is a sheep standing."], "negative_caption": ["There is no sheep standing."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2414848", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2414988.jpg", "positive_caption": ["There are elephants in the picture."], "negative_caption": ["There are no elephants in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2414988", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2415024.jpg", "positive_caption": ["There are windows around the vines."], "negative_caption": ["There are no windows around the vines."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2415024", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416322.jpg", "positive_caption": ["There are people wearing glasses."], "negative_caption": ["There are no people wearing glasses."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2416322", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2416742.jpg", "positive_caption": ["There are people visible."], "negative_caption": ["There are no people visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2416742", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713092.jpg", "positive_caption": ["There are buses."], "negative_caption": ["There are no buses."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_713092", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_713229.jpg", "positive_caption": ["There are maple leaves visible."], "negative_caption": ["There are no maple leaves visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_713229", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417412.jpg", "positive_caption": ["There are colors on the bird."], "negative_caption": ["There are no colors on the bird."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2417412", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2417320.jpg", "positive_caption": ["There are people in the photo."], "negative_caption": ["There are no people in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2417320", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315587.jpg", "positive_caption": ["There are planes."], "negative_caption": ["There are no planes."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2315587", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2315604.jpg", "positive_caption": ["There are sheep in the main pen."], "negative_caption": ["There are no sheep in the main pen."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2315604", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316070.jpg", "positive_caption": ["There are loaves."], "negative_caption": ["There are no loaves."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2316070", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2316226.jpg", "positive_caption": ["There are planes."], "negative_caption": ["There are no planes."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2316226", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2317071.jpg", "positive_caption": ["There are airplanes visible in the picture."], "negative_caption": ["There are no airplanes visible in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2317071", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318073.jpg", "positive_caption": ["There are lights."], "negative_caption": ["There are no lights."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2318073", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2318842.jpg", "positive_caption": ["There are knobs visible."], "negative_caption": ["There are no knobs visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2318842", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2319711.jpg", "positive_caption": ["There are tracks."], "negative_caption": ["There are no tracks."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2319711", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320007.jpg", "positive_caption": ["There are train tracks."], "negative_caption": ["There are no train tracks."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2320007", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2320264.jpg", "positive_caption": ["There are different fruits and veggies."], "negative_caption": ["There are no different fruits and veggies."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2320264", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323270.jpg", "positive_caption": ["There are players wearing long pants."], "negative_caption": ["There are no players wearing long pants."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2323270", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2323857.jpg", "positive_caption": ["There are kinds of fruit."], "negative_caption": ["There are no kinds of fruit."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2323857", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2324297.jpg", "positive_caption": ["There are children."], "negative_caption": ["There are no children."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2324297", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2325643.jpg", "positive_caption": ["There are people surfing."], "negative_caption": ["There are no people surfing."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2325643", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2326133.jpg", "positive_caption": ["You see street lights ."], "negative_caption": ["You see no street lights ."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2326133", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498210.jpg", "positive_caption": ["There are men."], "negative_caption": ["There are no men."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_498210", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328023.jpg", "positive_caption": ["There are cars parked."], "negative_caption": ["There are no cars parked."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2328023", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2328588.jpg", "positive_caption": ["There are oranges."], "negative_caption": ["There are no oranges."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2328588", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2331238.jpg", "positive_caption": ["There are sheep in the picture."], "negative_caption": ["There are no sheep in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2331238", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332306.jpg", "positive_caption": ["There are strings attached to the kite."], "negative_caption": ["There are no strings attached to the kite."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2332306", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2332478.jpg", "positive_caption": ["There are carrots in the photo."], "negative_caption": ["There are no carrots in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2332478", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_497990.jpg", "positive_caption": ["There are tourists."], "negative_caption": ["There are no tourists."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_497990", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_497995.jpg", "positive_caption": ["There are players wear red shorts."], "negative_caption": ["There are no players wear red shorts."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_497995", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_498214.jpg", "positive_caption": ["There are guys playing frisbee."], "negative_caption": ["There are no guys playing frisbee."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_498214", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333501.jpg", "positive_caption": ["There are cows shown."], "negative_caption": ["There are no cows shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2333501", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2333990.jpg", "positive_caption": ["There are servings on the plate."], "negative_caption": ["There are no servings on the plate."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2333990", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2334470.jpg", "positive_caption": ["There are snowboards in the photo."], "negative_caption": ["There are no snowboards in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2334470", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_107964.jpg", "positive_caption": ["There are men of four holding tennis rackets."], "negative_caption": ["There are no men of four holding tennis rackets."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_107964", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338295.jpg", "positive_caption": ["There are giraffes in this photo."], "negative_caption": ["There are no giraffes in this photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2338295", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2338787.jpg", "positive_caption": ["There are people in the picture."], "negative_caption": ["There are no people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2338787", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159384.jpg", "positive_caption": ["There are men who seated talking to each other."], "negative_caption": ["There are no men who seated talking to each other."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1159384", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159469.jpg", "positive_caption": ["There are beers on tap."], "negative_caption": ["There are no beers on tap."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1159469", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339363.jpg", "positive_caption": ["There are skis in the picture."], "negative_caption": ["There are no skis in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2339363", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339542.jpg", "positive_caption": ["There are vehicles visible."], "negative_caption": ["There are no vehicles visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2339542", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340065.jpg", "positive_caption": ["There are snow goggles in the picture."], "negative_caption": ["There are no snow goggles in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2340065", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2340140.jpg", "positive_caption": ["There is a trash cans shown."], "negative_caption": ["There is no trash cans shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2340140", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2342832.jpg", "positive_caption": ["There are giraffes."], "negative_caption": ["There are no giraffes."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2342832", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343200.jpg", "positive_caption": ["clasps can be closed on the case."], "negative_caption": ["No clasps can be closed on the case."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2343200", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343499.jpg", "positive_caption": ["There are blue stripes."], "negative_caption": ["There are no blue stripes."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2343499", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2343770.jpg", "positive_caption": ["There are cars."], "negative_caption": ["There are no cars."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2343770", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344828.jpg", "positive_caption": ["There are signs in the photo."], "negative_caption": ["There are no signs in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2344828", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2344996.jpg", "positive_caption": ["There are pillows."], "negative_caption": ["There are no pillows."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2344996", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378774.jpg", "positive_caption": ["There are people."], "negative_caption": ["There are no people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2378774", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345325.jpg", "positive_caption": ["There are surfers in the pic."], "negative_caption": ["There are no surfers in the pic."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2345325", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2345980.jpg", "positive_caption": ["There are red buildings shown on this street."], "negative_caption": ["There are no red buildings shown on this street."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2345980", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2346628.jpg", "positive_caption": ["There are players shown."], "negative_caption": ["There are no players shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2346628", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2347803.jpg", "positive_caption": ["There are workers on the scene."], "negative_caption": ["There are no workers on the scene."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2347803", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348430.jpg", "positive_caption": ["There are people on the closest court."], "negative_caption": ["There are no people on the closest court."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2348430", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2348772.jpg", "positive_caption": ["There are people."], "negative_caption": ["There are no people."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2348772", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2379676.jpg", "positive_caption": ["There are bikes."], "negative_caption": ["There are no bikes."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2379676", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2350818.jpg", "positive_caption": ["There are they."], "negative_caption": ["There are no they."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2350818", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351728.jpg", "positive_caption": ["There are doors visible."], "negative_caption": ["There are no doors visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2351728", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2351755.jpg", "positive_caption": ["There are beds in the room."], "negative_caption": ["There are no beds in the room."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2351755", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352132.jpg", "positive_caption": ["There are cars seen."], "negative_caption": ["There are no cars seen."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2352132", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2352174.jpg", "positive_caption": ["There are people visible."], "negative_caption": ["There are no people visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2352174", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2353180.jpg", "positive_caption": ["There are gummy bears on the remote."], "negative_caption": ["There are no gummy bears on the remote."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2353180", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2378548.jpg", "positive_caption": ["There are cars."], "negative_caption": ["There are no cars."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2378548", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2356992.jpg", "positive_caption": ["There are forks at each place setting."], "negative_caption": ["There are no forks at each place setting."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2356992", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357020.jpg", "positive_caption": ["There are people shown."], "negative_caption": ["There are no people shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2357020", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2357161.jpg", "positive_caption": ["There are animals."], "negative_caption": ["There are no animals."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2357161", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359039.jpg", "positive_caption": ["There are zebras facing right."], "negative_caption": ["There are no zebras facing right."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2359039", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2339375.jpg", "positive_caption": ["There are tennis players shown in the image."], "negative_caption": ["There are no tennis players shown in the image."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2339375", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359483.jpg", "positive_caption": ["There is a cat."], "negative_caption": ["There is no cat."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2359483", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2359944.jpg", "positive_caption": ["There is a person pictured."], "negative_caption": ["There is no person pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2359944", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360186.jpg", "positive_caption": ["There is a bird in the picture."], "negative_caption": ["There is no bird in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2360186", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360351.jpg", "positive_caption": ["There is a benche."], "negative_caption": ["There is no benche."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2360351", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360364.jpg", "positive_caption": ["There is a person."], "negative_caption": ["There is no person."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2360364", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360535.jpg", "positive_caption": ["There is a motorcycle in the picture."], "negative_caption": ["There is no motorcycle in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2360535", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360550.jpg", "positive_caption": ["There is a walking signs shown."], "negative_caption": ["There is no walking signs shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2360550", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2360625.jpg", "positive_caption": ["There is a motorcycle."], "negative_caption": ["There is no motorcycle."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2360625", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361000.jpg", "positive_caption": ["There is a person in the picture."], "negative_caption": ["There is no person in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361000", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361023.jpg", "positive_caption": ["There is a person."], "negative_caption": ["There is no person."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361023", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361093.jpg", "positive_caption": ["There is a person snowboarding."], "negative_caption": ["There is no person snowboarding."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361093", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361120.jpg", "positive_caption": ["There is a dishe."], "negative_caption": ["There is no dishe."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361120", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361201.jpg", "positive_caption": ["There is a horse."], "negative_caption": ["There is no horse."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361201", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361222.jpg", "positive_caption": ["There is a skier."], "negative_caption": ["There is no skier."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361222", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361671.jpg", "positive_caption": ["There is a person."], "negative_caption": ["There is no person."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361671", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361728.jpg", "positive_caption": ["There is a surfer."], "negative_caption": ["There is no surfer."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361728", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361872.jpg", "positive_caption": ["There are wheels visible on the plane."], "negative_caption": ["There are no wheels visible on the plane."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361872", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2361951.jpg", "positive_caption": ["There is a train in this picture."], "negative_caption": ["There is no train in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2361951", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362000.jpg", "positive_caption": ["There is a person in the photo."], "negative_caption": ["There is no person in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362000", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362033.jpg", "positive_caption": ["There is a motorcycle."], "negative_caption": ["There is no motorcycle."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362033", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362071.jpg", "positive_caption": ["There is a car pictured."], "negative_caption": ["There is no car pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362071", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362253.jpg", "positive_caption": ["There is a plane."], "negative_caption": ["There is no plane."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362253", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362651.jpg", "positive_caption": ["There are windows in the room."], "negative_caption": ["There are no windows in the room."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362651", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362750.jpg", "positive_caption": ["There is a person pictured."], "negative_caption": ["There is no person pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362750", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362804.jpg", "positive_caption": ["There is a dog."], "negative_caption": ["There is no dog."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362804", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2362825.jpg", "positive_caption": ["There is a woman."], "negative_caption": ["There is no woman."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2362825", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363189.jpg", "positive_caption": ["There is a benche."], "negative_caption": ["There is no benche."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363189", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363200.jpg", "positive_caption": ["There is a sliced."], "negative_caption": ["There is no sliced."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363200", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363335.jpg", "positive_caption": ["There is a mast on the closest boat."], "negative_caption": ["There is no mast on the closest boat."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363335", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363379.jpg", "positive_caption": ["There is a bird in this picture."], "negative_caption": ["There is no bird in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363379", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363425.jpg", "positive_caption": ["There is a person."], "negative_caption": ["There is no person."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363425", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363610.jpg", "positive_caption": ["There is a plane."], "negative_caption": ["There is no plane."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363610", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363617.jpg", "positive_caption": ["There is a pitcher visible."], "negative_caption": ["There is no pitcher visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363617", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363675.jpg", "positive_caption": ["There are window."], "negative_caption": ["There are no window."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363675", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363723.jpg", "positive_caption": ["There are lights on the sides of the bed."], "negative_caption": ["There are no lights on the sides of the bed."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363723", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2363773.jpg", "positive_caption": ["There is a person."], "negative_caption": ["There is no person."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2363773", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364196.jpg", "positive_caption": ["There is a person in the picture."], "negative_caption": ["There is no person in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2364196", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364632.jpg", "positive_caption": ["a trucks can be seen."], "negative_caption": ["No trucks can be seen."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2364632", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364722.jpg", "positive_caption": ["There is a computer pictured."], "negative_caption": ["There is no computer pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2364722", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364740.jpg", "positive_caption": ["There are people in the picture."], "negative_caption": ["There are no people in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2364740", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364769.jpg", "positive_caption": ["There is a laptop on the table."], "negative_caption": ["There is no laptop on the table."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2364769", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2364948.jpg", "positive_caption": ["There is a elephant in the picture."], "negative_caption": ["There is no elephant in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2364948", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365252.jpg", "positive_caption": ["There is a truck pictured."], "negative_caption": ["There is no truck pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2365252", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365320.jpg", "positive_caption": ["There is a teddy bears."], "negative_caption": ["There is no teddy bears."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2365320", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365399.jpg", "positive_caption": ["There is a train shown."], "negative_caption": ["There is no train shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2365399", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365480.jpg", "positive_caption": ["There is a chair."], "negative_caption": ["There is no chair."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2365480", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2365707.jpg", "positive_caption": ["There is a kite."], "negative_caption": ["There is no kite."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2365707", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366276.jpg", "positive_caption": ["There is a person shown."], "negative_caption": ["There is no person shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2366276", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366368.jpg", "positive_caption": ["There are small cups shown."], "negative_caption": ["There are no small cups shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2366368", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366431.jpg", "positive_caption": ["There is a tv."], "negative_caption": ["There is no tv."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2366431", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2366695.jpg", "positive_caption": ["There is a train."], "negative_caption": ["There is no train."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2366695", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367016.jpg", "positive_caption": ["There is a pencil shown."], "negative_caption": ["There is no pencil shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367016", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367084.jpg", "positive_caption": ["There is a giraffe."], "negative_caption": ["There is no giraffe."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367084", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367366.jpg", "positive_caption": ["There are people shown."], "negative_caption": ["There are no people shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367366", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367531.jpg", "positive_caption": ["There is a tub."], "negative_caption": ["There is no tub."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367531", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367700.jpg", "positive_caption": ["There is a flower pots."], "negative_caption": ["There is no flower pots."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367700", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367703.jpg", "positive_caption": ["There is a motorcycle."], "negative_caption": ["There is no motorcycle."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367703", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367736.jpg", "positive_caption": ["a apples can we clearly see in this photo."], "negative_caption": ["No apples can we clearly see in this photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367736", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367780.jpg", "positive_caption": ["There is a pizza."], "negative_caption": ["There is no pizza."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367780", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2367907.jpg", "positive_caption": ["There is a hand."], "negative_caption": ["There is no hand."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2367907", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368047.jpg", "positive_caption": ["There are plants by the fireplace."], "negative_caption": ["There are no plants by the fireplace."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2368047", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368127.jpg", "positive_caption": ["There is a horse in the picture."], "negative_caption": ["There is no horse in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2368127", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368433.jpg", "positive_caption": ["There is a person pictured."], "negative_caption": ["There is no person pictured."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2368433", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368470.jpg", "positive_caption": ["There are bananas."], "negative_caption": ["There are no bananas."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2368470", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368830.jpg", "positive_caption": ["There is a clock."], "negative_caption": ["There is no clock."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2368830", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368862.jpg", "positive_caption": ["There is a horse."], "negative_caption": ["There is no horse."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2368862", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368971.jpg", "positive_caption": ["There is a clock shown."], "negative_caption": ["There is no clock shown."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2368971", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2368996.jpg", "positive_caption": ["There are eyes of the bird in the photo."], "negative_caption": ["There are no eyes of the bird in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2368996", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_1159443.jpg", "positive_caption": ["There are old men."], "negative_caption": ["There are no old men."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_1159443", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369455.jpg", "positive_caption": ["There is a baseball players in the photo."], "negative_caption": ["There is no baseball players in the photo."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2369455", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2369718.jpg", "positive_caption": ["There is a dog."], "negative_caption": ["There is no dog."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2369718", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370072.jpg", "positive_caption": ["There are people pictured here."], "negative_caption": ["There are no people pictured here."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370072", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370194.jpg", "positive_caption": ["There is a giraffe."], "negative_caption": ["There is no giraffe."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370194", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370341.jpg", "positive_caption": ["There is a teddy bears."], "negative_caption": ["There is no teddy bears."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370341", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370415.jpg", "positive_caption": ["There is a dog in the water."], "negative_caption": ["There is no dog in the water."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370415", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370551.jpg", "positive_caption": ["There is a horse."], "negative_caption": ["There is no horse."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370551", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370565.jpg", "positive_caption": ["There is a giraffe."], "negative_caption": ["There is no giraffe."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370565", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2370926.jpg", "positive_caption": ["There is a player visible."], "negative_caption": ["There is no player visible."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2370926", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371067.jpg", "positive_caption": ["There is a skater."], "negative_caption": ["There is no skater."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371067", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371443.jpg", "positive_caption": ["There is a skateboarder in the picture."], "negative_caption": ["There is no skateboarder in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371443", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371468.jpg", "positive_caption": ["There is a vehicle."], "negative_caption": ["There is no vehicle."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371468", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371491.jpg", "positive_caption": ["There is a person in the picture."], "negative_caption": ["There is no person in the picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371491", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371495.jpg", "positive_caption": ["There is a person in this picture."], "negative_caption": ["There is no person in this picture."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371495", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371625.jpg", "positive_caption": ["There is a person."], "negative_caption": ["There is no person."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371625", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "visual7w/v7w_2371901.jpg", "positive_caption": ["There is a green objects on the floor."], "negative_caption": ["There is no green objects on the floor."], "original_file_name": "existence", "dataset": "visual7w", "key": "existence_visual7w_2371901", "linguistic_phenomena": "existence", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000165831.jpg", "positive_caption": ["a giant bowl of food, with broccoli and other food on it."], "negative_caption": ["a giant bottle of food, with broccoli and other food on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1283539", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000074369.jpg", "positive_caption": ["a young boy posing with a basebat bat in hand"], "negative_caption": ["a young boy posing with a baseball ball in hand"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1006085", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000158372.jpg", "positive_caption": ["a blue closed suitcase sitting on a white table."], "negative_caption": ["a blue closed suitcase sitting on a white bed."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1100983", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000341818.jpg", "positive_caption": ["a man who is sitting at a table with a plate in front of him."], "negative_caption": ["a man who is sitting at a chair with a plate in front of him."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1147071", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000382584.jpg", "positive_caption": ["a transit bus making a turn into a garage of some sort."], "negative_caption": ["a transit airplane making a turn into a garage of some sort."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1204198", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000025165.jpg", "positive_caption": ["a hand holding a remote control next to a bottle of pills."], "negative_caption": ["a hand holding a remote control next to a cup of pills."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1253685", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000245764.jpg", "positive_caption": ["a cat sits on the edge of a toilet."], "negative_caption": ["a dog sits on the edge of a toilet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1211094", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000416105.jpg", "positive_caption": ["the man is swinging a tennis racket while jumping"], "negative_caption": ["the man is swinging a tennis ball while jumping"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1132873", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000501142.jpg", "positive_caption": ["a cow partially submerged standing near a body of water"], "negative_caption": ["a dog partially submerged standing near a body of water"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1085458", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000504932.jpg", "positive_caption": ["beef and broccoli with broccolis on a plate."], "negative_caption": ["beef and carrot with carrots on a plate."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1199735", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000134552.jpg", "positive_caption": ["a woman in a tennis outfit holds a racket."], "negative_caption": ["a woman in a tennis outfit holds a ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1074776", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000026768.jpg", "positive_caption": ["two kittens sitting on a laptop with one in the middle of the key board and one sitting half on the side of the key board and half on the desk."], "negative_caption": ["two kittens sitting on a tv with one in the middle of the key board and one sitting half on the side of the key board and half on the desk."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1289118", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000579815.jpg", "positive_caption": ["a man holding an open umbrella near tall buildings."], "negative_caption": ["a man holding an open tie near tall buildings."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1002921", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000083850.jpg", "positive_caption": ["that pizza is four times the size of a normal pizza."], "negative_caption": ["that pizza is four times the size of a normal sandwich."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1261127", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000550597.jpg", "positive_caption": ["a white sink sitting next to a toilet near a tub."], "negative_caption": ["a white refrigerator sitting next to a toilet near a tub."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1015147", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000156607.jpg", "positive_caption": ["cow laying by lake while another cow walks in grass"], "negative_caption": ["cow laying by lake while another zebra walks in grass"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1129948", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000381630.jpg", "positive_caption": ["view of city and train moving on tracks."], "negative_caption": ["view of city and bus moving on tracks."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1190802", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000277587.jpg", "positive_caption": ["a big bed with a lot of pillows on it"], "negative_caption": ["a big couch with a lot of pillows on it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1201137", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000438704.jpg", "positive_caption": ["at the picture is a scene of an airplane outside of a town."], "negative_caption": ["at the picture is a scene of an truck outside of a town."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1121441", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000214958.jpg", "positive_caption": ["a young person drags a surfboard through the water on the beach."], "negative_caption": ["a young person drags a kite through the water on the beach."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1215311", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000421131.jpg", "positive_caption": ["a pair of young men sit on a case beside a motorcycle."], "negative_caption": ["a pair of young men sit on a case beside a bicycle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1053332", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000243464.jpg", "positive_caption": ["a man standing next to a woman near a giraffe."], "negative_caption": ["a man standing next to a woman near a zebra."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1121628", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000297787.jpg", "positive_caption": ["a woman with dread locks in a kitchen beside a wall of knives and scissors."], "negative_caption": ["a woman with dread locks in a kitchen beside a wall of knives and vase."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1044799", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000180784.jpg", "positive_caption": ["an older model airplane is parked in a field."], "negative_caption": ["an older model truck is parked in a field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1083935", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000464200.jpg", "positive_caption": ["a woman holding a white frisbee standing next to a rusted net."], "negative_caption": ["a woman holding a white racket standing next to a rusted net."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1176254", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000362469.jpg", "positive_caption": ["a boat that is sitting in the water."], "negative_caption": ["a airplane that is sitting in the water."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1235831", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000357356.jpg", "positive_caption": ["a young man is throwing a frisbee up in the air and catching it between a house entryway with a railing and a garden area with steps."], "negative_caption": ["a young man is throwing a ball up in the air and catching it between a house entryway with a railing and a garden area with steps."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1033374", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000096633.jpg", "positive_caption": ["a brown bear sitting up against a tree on a green grass covered field."], "negative_caption": ["a brown horse sitting up against a tree on a green grass covered field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1216720", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000423892.jpg", "positive_caption": ["children and a lady are looking at a lit birthday cake."], "negative_caption": ["children and a lady are looking at a lit birthday pizza."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1185443", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000184810.jpg", "positive_caption": ["a man laughing while holding a surfboard on the beach."], "negative_caption": ["a man laughing while holding a kite on the beach."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1049775", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000031521.jpg", "positive_caption": ["a person that is on a laptop on a table"], "negative_caption": ["a person that is on a laptop on a chair"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1260909", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000554620.jpg", "positive_caption": ["woman in purple jacket holding a white and blue umbrella."], "negative_caption": ["woman in purple jacket holding a white and blue tie."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1138152", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000575637.jpg", "positive_caption": ["a man paddles a boat while his passenger relaxes in the back."], "negative_caption": ["a man paddles a truck while his passenger relaxes in the back."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1273392", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000462840.jpg", "positive_caption": ["a dog is sitting in the bed of a moving truck near traffic."], "negative_caption": ["a bear is sitting in the bed of a moving truck near traffic."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1077935", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000180751.jpg", "positive_caption": ["a man in an orange shirt pouring a glass of wine at a wine bar."], "negative_caption": ["a man in an orange shirt pouring a cup of wine at a wine bar."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1142162", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000522108.jpg", "positive_caption": ["a new refrigerator was delivered with the plastic still wrapped around it."], "negative_caption": ["a new microwave was delivered with the plastic still wrapped around it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1149172", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000367578.jpg", "positive_caption": ["a man in a tie waits in a room full of people."], "negative_caption": ["a man in a suitcase waits in a room full of people."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1025525", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000014297.jpg", "positive_caption": ["a house boat with many bikes on a riverbank."], "negative_caption": ["a house truck with many bikes on a riverbank."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1090996", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000494141.jpg", "positive_caption": ["a glass display cabinet with various bagels, doughnuts, muffins"], "negative_caption": ["a cup display cabinet with various bagels, doughnuts, muffins"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1223116", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000429593.jpg", "positive_caption": ["a room filled with furniture and a tv."], "negative_caption": ["a room filled with furniture and a phone."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1186322", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000551780.jpg", "positive_caption": ["a clock on a building that says 8:25."], "negative_caption": ["a book on a building that says 8:25."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1118017", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000551822.jpg", "positive_caption": ["a french dip sandwich that is on a plate."], "negative_caption": ["a french dip pizza that is on a plate."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1103199", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000391774.jpg", "positive_caption": ["a toddler playing with toy trains on a toilet."], "negative_caption": ["a toddler playing with toy trains on a bed."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1248478", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000409701.jpg", "positive_caption": ["a mother bird feeds her little baby chicks."], "negative_caption": ["a mother cat feeds her little baby chicks."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1295155", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000309044.jpg", "positive_caption": ["a living room with a cat sitting on the carpet"], "negative_caption": ["a living room with a dog sitting on the carpet"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1221129", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000032322.jpg", "positive_caption": ["a row of cupboards in the wall above a refrigerator."], "negative_caption": ["a row of cupboards in the wall above a microwave."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1209770", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000354744.jpg", "positive_caption": ["an abandoned boat sits on the shore of a beach."], "negative_caption": ["an abandoned airplane sits on the shore of a beach."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1039938", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000440023.jpg", "positive_caption": ["a plate with a sandwich cut in half."], "negative_caption": ["a plate with a pizza cut in half."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1274648", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000355974.jpg", "positive_caption": ["a man bending over to use a child's laptop computer."], "negative_caption": ["a man bending over to use a child's tv computer."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1082295", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000344325.jpg", "positive_caption": ["helmeted person taking a tight corner on a motorcycle."], "negative_caption": ["helmeted person taking a tight corner on a bicycle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1263741", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000067868.jpg", "positive_caption": ["an orange bench surrounded by flood waters near a small metal grill."], "negative_caption": ["an orange hydrant surrounded by flood waters near a small metal grill."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1001125", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000311394.jpg", "positive_caption": ["a child holds a toothbrush in their hand."], "negative_caption": ["a child holds a drier in their hand."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1021086", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000286362.jpg", "positive_caption": ["a ginger holding up a fist next to a ripe banana."], "negative_caption": ["a ginger holding up a fist next to a ripe carrot."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1123980", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000012326.jpg", "positive_caption": ["this kitchen contains a stove with an exhaust hood, many cabinets, and a microwave."], "negative_caption": ["this kitchen contains a stove with an exhaust hood, many cabinets, and a sink."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1127858", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000093261.jpg", "positive_caption": ["a young man on the beach assembling a kite."], "negative_caption": ["a young man on the beach assembling a surfboard."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1119365", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000393372.jpg", "positive_caption": ["a woman in a black dress shirt and tie with purple hair."], "negative_caption": ["a woman in a black dress shirt and suitcase with purple hair."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1191637", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000304484.jpg", "positive_caption": ["a dining room has a grandfather clock in the corner."], "negative_caption": ["a dining room has a grandfather book in the corner."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1187843", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000531349.jpg", "positive_caption": ["a double decker bus parked by the water"], "negative_caption": ["a double decker bicycle parked by the water"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1084475", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000129897.jpg", "positive_caption": ["four men sit at a table with dishes and beers in front of them."], "negative_caption": ["four men sit at a bed with dishes and beers in front of them."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1157379", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000578383.jpg", "positive_caption": ["a black and white cow and some white birds and water"], "negative_caption": ["a black and white elephant and some white birds and water"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1039913", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000456833.jpg", "positive_caption": ["a grey and red train in the middle of a street."], "negative_caption": ["a grey and red bus in the middle of a street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1250131", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000259571.jpg", "positive_caption": ["an orange truck driving down a street full of men in the back."], "negative_caption": ["an orange car driving down a street full of men in the back."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1031191", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000213525.jpg", "positive_caption": ["a cloth covered plate of donuts next to a glass of milk."], "negative_caption": ["a cloth covered plate of donuts next to a cup of milk."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1064923", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000029357.jpg", "positive_caption": ["a sliced whole pizza with red peppers on a white plate."], "negative_caption": ["a sliced whole sandwich with red peppers on a white plate."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1118776", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000475223.jpg", "positive_caption": ["a bird is eating a frog in a marsh."], "negative_caption": ["a cat is eating a frog in a marsh."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1288157", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000432293.jpg", "positive_caption": ["a hand tossed pizza is shown on a pizza board"], "negative_caption": ["a hand tossed pizza is shown on a sandwich board"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1013950", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000294776.jpg", "positive_caption": ["a beautiful woman putting a frisbee inside of a metal net."], "negative_caption": ["a beautiful woman putting a racket inside of a metal net."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1176238", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000084567.jpg", "positive_caption": ["statute of a horse and rider on top of a block wall."], "negative_caption": ["statute of a bird and rider on top of a block wall."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1068671", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000313182.jpg", "positive_caption": ["a purple and white bus driving down a street."], "negative_caption": ["a purple and white motorcycle driving down a street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1060543", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000438539.jpg", "positive_caption": ["various images of a girl playing with a frisbee."], "negative_caption": ["various images of a girl playing with a ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1258886", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000545903.jpg", "positive_caption": ["a room with a bed, slippers and oval bowl."], "negative_caption": ["a room with a couch, slippers and oval bowl."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1170662", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000360350.jpg", "positive_caption": ["a person holds a surfboard on his shoulders."], "negative_caption": ["a person holds a kite on his shoulders."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1200454", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000029776.jpg", "positive_caption": ["a man riding a red motorcycle next to buildings in front of a street."], "negative_caption": ["a man riding a red bicycle next to buildings in front of a street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1287162", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000296676.jpg", "positive_caption": ["some people and a woman with a red frisbee"], "negative_caption": ["some people and a woman with a red snowboard"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1145736", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000550702.jpg", "positive_caption": ["there are many different plates of food on the table"], "negative_caption": ["there are many different plates of food on the chair"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1041654", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000048636.jpg", "positive_caption": ["the boy hits the basebat with a bat."], "negative_caption": ["the boy hits the baseball with a ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1006054", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000207937.jpg", "positive_caption": ["a person with a blue, red, and green plaid umbrella"], "negative_caption": ["a person with a blue, red, and green plaid tie"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1048055", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000525381.jpg", "positive_caption": ["a batter at home plate swinging his basebat bat"], "negative_caption": ["a batter at home plate swinging his baseball ball"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1058913", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000485896.jpg", "positive_caption": ["a large group of men on horse back carrying flags."], "negative_caption": ["a large group of men on cow back carrying flags."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1026271", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000234387.jpg", "positive_caption": ["three donuts sit in a box on the back of a bicycle."], "negative_caption": ["three donuts sit in a box on the back of a motorcycle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1049676", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000259853.jpg", "positive_caption": ["children sitting at a table eating and drinking."], "negative_caption": ["children sitting at a bed eating and drinking."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1042222", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000238292.jpg", "positive_caption": ["a tropical bird on a tree with a nut in its mouth."], "negative_caption": ["a tropical sheep on a tree with a nut in its mouth."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1197124", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000041077.jpg", "positive_caption": ["a man flying through the air while riding a snowboard."], "negative_caption": ["a man flying through the air while riding a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1215167", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000406097.jpg", "positive_caption": ["a field full of lots of yellow flowers with a train passing it by."], "negative_caption": ["a field full of lots of yellow flowers with a bus passing it by."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1151451", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000087409.jpg", "positive_caption": ["three women are on a boat in the water."], "negative_caption": ["three women are on a motorcycle in the water."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1223248", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000376295.jpg", "positive_caption": ["a man and child sitting around a birthday cake."], "negative_caption": ["a man and child sitting around a birthday pizza."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1260664", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000486484.jpg", "positive_caption": ["a close up of dog with its head between a fence"], "negative_caption": ["a close up of bird with its head between a fence"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1071827", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000227359.jpg", "positive_caption": ["a student using both a book and computer to study."], "negative_caption": ["a student using both a scissors and computer to study."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1013043", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000409491.jpg", "positive_caption": ["people in a park and a man trying to fly his kite."], "negative_caption": ["people in a park and a man trying to fly his frisbee."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1028684", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000144715.jpg", "positive_caption": ["a train sitting on top of train tracks near forest."], "negative_caption": ["a truck sitting on top of train tracks near forest."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1039133", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000120792.jpg", "positive_caption": ["two men standing in front of a tv playing with a wii."], "negative_caption": ["two men standing in front of a remote playing with a wii."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1292105", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000046805.jpg", "positive_caption": ["a car at on intersection who has the green light"], "negative_caption": ["a bicycle at on intersection who has the green light"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1166307", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000217622.jpg", "positive_caption": ["man on surfboard riding crested wave into shore"], "negative_caption": ["man on snowboard riding crested wave into shore"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1170364", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000413079.jpg", "positive_caption": ["a person riding on a horse while jumping it over an obstacle."], "negative_caption": ["a person riding on a cow while jumping it over an obstacle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1072122", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000017534.jpg", "positive_caption": ["two men are playing tennis one of them is serving the ball."], "negative_caption": ["two men are playing tennis one of them is serving the glove."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1028959", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000116845.jpg", "positive_caption": ["a wood table full of vegetables and fruits on it"], "negative_caption": ["a wood chair full of vegetables and fruits on it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1177337", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000405635.jpg", "positive_caption": ["a bedroom with large bed and windows and chair."], "negative_caption": ["a bedroom with large bed and windows and table."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1253231", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000005154.jpg", "positive_caption": ["a long skinny bed with a floral blanket on it"], "negative_caption": ["a long skinny couch with a floral blanket on it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1253379", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000185903.jpg", "positive_caption": ["train carts captured from out of a train window."], "negative_caption": ["airplane carts captured from out of a train window."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1190512", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000166541.jpg", "positive_caption": ["a train moving along the rail with many besides"], "negative_caption": ["a bus moving along the rail with many besides"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1281102", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000087356.jpg", "positive_caption": ["a bus with a bike rack on the front of it"], "negative_caption": ["a airplane with a bike rack on the front of it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1061125", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000279919.jpg", "positive_caption": ["a cat that is playing with a fake banana"], "negative_caption": ["a cat that is playing with a fake carrot"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1062896", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000013383.jpg", "positive_caption": ["two cats sleeping on a table by a coffee cup"], "negative_caption": ["two cats sleeping on a table by a coffee bottle"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1002082", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000107853.jpg", "positive_caption": ["a person doing tricks on a skateboard near a railing that runs next to a road."], "negative_caption": ["a person doing tricks on a kite near a railing that runs next to a road."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1073083", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000220764.jpg", "positive_caption": ["a person riding skis across snow covered ground."], "negative_caption": ["a person riding snowboard across snow covered ground."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1095169", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000251892.jpg", "positive_caption": ["an assortment of foods in bowls, drinks and condiments on a table."], "negative_caption": ["an assortment of foods in bowls, drinks and condiments on a bed."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1075724", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000188290.jpg", "positive_caption": ["the train engine is different than the ones we have in the usa."], "negative_caption": ["the bus engine is different than the ones we have in the usa."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1070129", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000160607.jpg", "positive_caption": ["a child playing with a red frisbee in a park."], "negative_caption": ["a child playing with a red ball in a park."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1236546", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000255691.jpg", "positive_caption": ["a man sitting in front of a tv holding his hand up."], "negative_caption": ["a man sitting in front of a remote holding his hand up."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1285610", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000153217.jpg", "positive_caption": ["a cat walks next to a motorcycle on a sidewalk."], "negative_caption": ["a dog walks next to a motorcycle on a sidewalk."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1083584", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000019275.jpg", "positive_caption": ["two children sitting at a table and eating cake."], "negative_caption": ["two children sitting at a table and eating pizza."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1170438", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000375915.jpg", "positive_caption": ["pizza on a tray on the table outside next to plates and wine glass"], "negative_caption": ["sandwich on a tray on the table outside next to plates and wine glass"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1201972", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000483722.jpg", "positive_caption": ["an electric commuter train emerging from a tunnel"], "negative_caption": ["an electric commuter bus emerging from a tunnel"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1062074", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000281387.jpg", "positive_caption": ["a dinner table with a place setting and dish of food that has meat and vegetables."], "negative_caption": ["a dinner bed with a place setting and dish of food that has meat and vegetables."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1124628", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000051326.jpg", "positive_caption": ["three decorated, carved jack-o-lanterns, one with pink flowers and a vase inside it"], "negative_caption": ["three decorated, carved jack-o-lanterns, one with pink flowers and a clock inside it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1105437", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000387250.jpg", "positive_caption": ["the young boy is eating a donut in the kitchen."], "negative_caption": ["the young boy is eating a banana in the kitchen."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1103217", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000040757.jpg", "positive_caption": ["a young boy laying in bed with a pacifier in his mouth"], "negative_caption": ["a young boy laying in couch with a pacifier in his mouth"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1073872", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000287443.jpg", "positive_caption": ["a plate of food, with broccoli and nuts."], "negative_caption": ["a plate of food, with carrot and nuts."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1267564", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000226360.jpg", "positive_caption": ["cat drinking from metal bowl on top of wood fence."], "negative_caption": ["cat drinking from metal bottle on top of wood fence."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1060538", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000097146.jpg", "positive_caption": ["large clock tower on top of a large city building."], "negative_caption": ["large book tower on top of a large city building."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1120183", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000154254.jpg", "positive_caption": ["a man with a laptop is next to a cat."], "negative_caption": ["a man with a laptop is next to a dog."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1032122", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000466422.jpg", "positive_caption": ["person with a number twenty four jersey at the bat during a basebat game."], "negative_caption": ["person with a number twenty four jersey at the ball during a baseball game."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1187118", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000575719.jpg", "positive_caption": ["a woman near a lake holding a frisbee with her thumbs."], "negative_caption": ["a woman near a lake holding a racket with her thumbs."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1094786", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000261333.jpg", "positive_caption": ["a black cat taking a drink out of a bright blue cup."], "negative_caption": ["a black cat taking a drink out of a bright blue bottle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1167539", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000071360.jpg", "positive_caption": ["a teary eyed baby is holding a toothbrush."], "negative_caption": ["a teary eyed baby is holding a drier."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1066030", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000297037.jpg", "positive_caption": ["a person rides a horse down a sunny beach."], "negative_caption": ["a person rides a cow down a sunny beach."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1252129", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000022755.jpg", "positive_caption": ["a big yellow school bus shown through the rear view of another school bus"], "negative_caption": ["a big yellow school bicycle shown through the rear view of another school bus"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1166334", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000379584.jpg", "positive_caption": ["some sheep stand outside a wooden plank building."], "negative_caption": ["some cow stand outside a wooden plank building."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1219783", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000136718.jpg", "positive_caption": ["a girl sits and looks at the screen of the laptop computer."], "negative_caption": ["a girl sits and looks at the screen of the tv computer."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1043804", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000240275.jpg", "positive_caption": ["a man is riding a surfboard at the beach"], "negative_caption": ["a man is riding a kite at the beach"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1118575", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000057454.jpg", "positive_caption": ["there are three urinals and a toilet in the bathroom"], "negative_caption": ["there are three urinals and a table in the bathroom"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1241456", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000015155.jpg", "positive_caption": ["a piece of cake sitting on top of a white plate."], "negative_caption": ["a piece of sandwich sitting on top of a white plate."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1237924", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000366099.jpg", "positive_caption": ["a pizza with many toppings and mozzarella cheese."], "negative_caption": ["a sandwich with many toppings and mozzarella cheese."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1208476", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000274591.jpg", "positive_caption": ["a bear stands on all fours near rocks and fallen trees."], "negative_caption": ["a cat stands on all fours near rocks and fallen trees."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1176526", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000081738.jpg", "positive_caption": ["someone about to cut and birthday cake with blue and yellow frosting."], "negative_caption": ["someone about to cut and birthday pizza with blue and yellow frosting."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1230193", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000105872.jpg", "positive_caption": ["a large group of children and adults lined up to board a double decker bus."], "negative_caption": ["a large group of children and adults lined up to board a double decker bicycle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1038540", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000486774.jpg", "positive_caption": ["a man is riding a surfboard on the water of ocean."], "negative_caption": ["a man is riding a frisbee on the water of ocean."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1096372", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000231828.jpg", "positive_caption": ["a facial shot of a giraffe sitting in it's area."], "negative_caption": ["a facial shot of a zebra sitting in it's area."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1077196", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000581458.jpg", "positive_caption": ["there is a crossing guard that is standing under the train tracks"], "negative_caption": ["there is a crossing guard that is standing under the bus tracks"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1242534", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000478798.jpg", "positive_caption": ["a woman standing in a store playing iwth a kids laptop"], "negative_caption": ["a woman standing in a store playing iwth a kids tv"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1262209", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000062410.jpg", "positive_caption": ["a vase filled with white orchids in the window of a restaurant."], "negative_caption": ["a toothbrush filled with white orchids in the window of a restaurant."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1090373", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000574796.jpg", "positive_caption": ["a bowl filled with, fruit, crackers and greens."], "negative_caption": ["a knife filled with, fruit, crackers and greens."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1011251", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000164899.jpg", "positive_caption": ["a plate of food is pictured on a table, with another person sitting opposite."], "negative_caption": ["a plate of food is pictured on a chair, with another person sitting opposite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1029590", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000377951.jpg", "positive_caption": ["a female action figurine sitting on a table next to a glass of water and pizza"], "negative_caption": ["a female action figurine sitting on a table next to a glass of water and sandwich"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1112105", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000102598.jpg", "positive_caption": ["a dog catching a flying frisbee in the snow."], "negative_caption": ["a dog catching a flying snowboard in the snow."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1055818", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000277518.jpg", "positive_caption": ["birds are standing on an old boat that is tied to the shore."], "negative_caption": ["birds are standing on an old airplane that is tied to the shore."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1024419", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000244539.jpg", "positive_caption": ["classic motorcycle on its stand with sign in front."], "negative_caption": ["classic car on its stand with sign in front."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1181229", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000434886.jpg", "positive_caption": ["a child holding a baseball bat posing for a picture."], "negative_caption": ["a child holding a baseball kite posing for a picture."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1148448", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000506095.jpg", "positive_caption": ["a cat is staring at a laptop computer."], "negative_caption": ["a cat is staring at a mouse computer."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1175097", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000166696.jpg", "positive_caption": ["a basebakl player runs around the bases as a ball is thrown to a fielder."], "negative_caption": ["a basebakl player runs around the bases as a glove is thrown to a fielder."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1064149", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000394157.jpg", "positive_caption": ["a white cat wall clock with a red handle"], "negative_caption": ["a white horse wall clock with a red handle"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1168091", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000474272.jpg", "positive_caption": ["an image of a dog jumping up at the camera"], "negative_caption": ["an image of a bear jumping up at the camera"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1290036", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000170729.jpg", "positive_caption": ["a young lady sitting at a table covered in food."], "negative_caption": ["a young lady sitting at a bed covered in food."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1208266", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000045830.jpg", "positive_caption": ["a black cat laying on top of a suitcase in a room."], "negative_caption": ["a black dog laying on top of a suitcase in a room."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1265387", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000081061.jpg", "positive_caption": ["a chair, couch and suitcase sitting by the road"], "negative_caption": ["a chair, bed and suitcase sitting by the road"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1266469", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000465718.jpg", "positive_caption": ["a table with so many screen and a keyboard"], "negative_caption": ["a bed with so many screen and a keyboard"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1089873", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000341567.jpg", "positive_caption": ["black bird flying over a rocky and snowy landscape."], "negative_caption": ["black dog flying over a rocky and snowy landscape."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1077475", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000148724.jpg", "positive_caption": ["short commuter train passing an outdoor platform, on off hours."], "negative_caption": ["short commuter airplane passing an outdoor platform, on off hours."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1182088", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000279723.jpg", "positive_caption": ["a woman with a space shuttle patch checking her cell phone."], "negative_caption": ["a woman with a space shuttle patch checking her cell keyboard."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1097605", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000441471.jpg", "positive_caption": ["a person sitting at a table with an ikeyboard, keyboard and using a tablet."], "negative_caption": ["a person sitting at a table with an iphone, phone and using a tablet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1268731", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000543547.jpg", "positive_caption": ["a man walks beside an elephant as people ride by on the street."], "negative_caption": ["a man walks beside an horse as people ride by on the street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1236367", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000420914.jpg", "positive_caption": ["a beautiful white dog standing in a grassy yard by a chair."], "negative_caption": ["a beautiful white bird standing in a grassy yard by a chair."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1108881", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000281800.jpg", "positive_caption": ["a boy ramping a skateboard over a box."], "negative_caption": ["a boy ramping a bat over a box."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1139560", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000563882.jpg", "positive_caption": ["a woman sitting in a seat holding a cell phone."], "negative_caption": ["a woman sitting in a seat holding a cell laptop."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1090109", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000452784.jpg", "positive_caption": ["a person washing something under the running water of a faucet next to a bowl of greens."], "negative_caption": ["a person washing something under the running water of a faucet next to a glass of greens."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1154479", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000176017.jpg", "positive_caption": ["three women who are eating something from a bowl."], "negative_caption": ["three women who are eating something from a glass."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1172414", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000252617.jpg", "positive_caption": ["a cat is hiding inside a purse."], "negative_caption": ["a dog is hiding inside a purse."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1271515", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000143445.jpg", "positive_caption": ["a woman drinking a small glass of wine."], "negative_caption": ["a woman drinking a small cup of wine."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1255573", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000483330.jpg", "positive_caption": ["a colorful dish of broccoli and macaroni in a black container."], "negative_caption": ["a colorful dish of carrot and macaroni in a black container."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1259580", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000468505.jpg", "positive_caption": ["dude ecstatic sitting by himself at a table full of food."], "negative_caption": ["dude ecstatic sitting by himself at a bed full of food."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1103105", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000363325.jpg", "positive_caption": ["a cat with its head in a box of pizza"], "negative_caption": ["a cat with its head in a box of carrot"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1137276", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000121152.jpg", "positive_caption": ["a red and white bus sits below a blue overpass."], "negative_caption": ["a red and white motorcycle sits below a blue overpass."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1084695", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000397403.jpg", "positive_caption": ["a bird standing on a tree limb next to its nest"], "negative_caption": ["a cat standing on a tree limb next to its nest"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1211990", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000159970.jpg", "positive_caption": ["a couple of kids laying on top of a bed."], "negative_caption": ["a couple of kids laying on top of a couch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1096196", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000527060.jpg", "positive_caption": ["a group of people around a chocolate cake with candles."], "negative_caption": ["a group of people around a chocolate pizza with candles."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1113268", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000449150.jpg", "positive_caption": ["a gray stripped cat holds its face toward a red toothbrush."], "negative_caption": ["a gray stripped dog holds its face toward a red toothbrush."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1236221", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000560675.jpg", "positive_caption": ["the large train is painted yellow, blue, and grey."], "negative_caption": ["the large airplane is painted yellow, blue, and grey."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1039524", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000297698.jpg", "positive_caption": ["a man on skis fly through the sky"], "negative_caption": ["a man on skateboard fly through the sky"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1048876", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000139749.jpg", "positive_caption": ["umbrella hanging fron the ceiling of a terminal"], "negative_caption": ["tie hanging fron the ceiling of a terminal"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1047763", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000105261.jpg", "positive_caption": ["a subway train at a train stop light."], "negative_caption": ["a subway bus at a train stop light."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1190381", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000083844.jpg", "positive_caption": ["a sign a street a green car and a person with a black umbrella"], "negative_caption": ["a sign a street a green car and a person with a black backpack"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1083516", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000210439.jpg", "positive_caption": ["a young man catching a blue frisbee in a park."], "negative_caption": ["a young man catching a blue ball in a park."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1094666", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000160933.jpg", "positive_caption": ["a man smile at a table with a pizza on it"], "negative_caption": ["a man smile at a bed with a pizza on it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1096410", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000010138.jpg", "positive_caption": ["a man is sitting in front of a small cake"], "negative_caption": ["a man is sitting in front of a small pizza"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1185712", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000041273.jpg", "positive_caption": ["a black cat sits in the upper portion of a filled suitcase."], "negative_caption": ["a black elephant sits in the upper portion of a filled suitcase."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1257552", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000344860.jpg", "positive_caption": ["a zebra looks over another zebra in the grass."], "negative_caption": ["a zebra looks over another giraffe in the grass."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1003408", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000205906.jpg", "positive_caption": ["phones, watches and clocks laying on a table."], "negative_caption": ["phones, watches and clocks laying on a bed."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1293021", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000522909.jpg", "positive_caption": ["a grey cat sitting on wooden box in sunlight of window."], "negative_caption": ["a grey dog sitting on wooden box in sunlight of window."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1062623", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000376416.jpg", "positive_caption": ["a group of basebat players holding a bat."], "negative_caption": ["a group of baseball players holding a ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1292415", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000416663.jpg", "positive_caption": ["a cat has its head close to a computer keyboard."], "negative_caption": ["a giraffe has its head close to a computer keyboard."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1198095", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000254965.jpg", "positive_caption": ["a giraffe bends down and eats grasses."], "negative_caption": ["a horse bends down and eats grasses."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1294608", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000274653.jpg", "positive_caption": ["a double layer cake decorated for christmas with white frosting and penguins."], "negative_caption": ["a double layer pizza decorated for christmas with white frosting and penguins."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1238259", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000149022.jpg", "positive_caption": ["a close up of a plate of doughnuts on a table"], "negative_caption": ["a close up of a plate of doughnuts on a bed"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1080464", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000430259.jpg", "positive_caption": ["a man in white shirt on cellphone with a tiny umbrella extension."], "negative_caption": ["a man in white shirt on cellphone with a tiny tie extension."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1029304", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000181542.jpg", "positive_caption": ["a woman in white crosses the road against the flow of motorcycle traffic."], "negative_caption": ["a woman in white crosses the road against the flow of bicycle traffic."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1188570", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000347144.jpg", "positive_caption": ["three people, one in uniform wearing a hat, are holding a sword above a birthday cake."], "negative_caption": ["three people, one in uniform wearing a hat, are holding a sword above a birthday pizza."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1080653", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000311435.jpg", "positive_caption": ["the man is just getting ready to serve the tennis ball."], "negative_caption": ["the man is just getting ready to serve the tennis racket."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1231149", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000578099.jpg", "positive_caption": ["a blue motorcycle is parked on a side walk."], "negative_caption": ["a blue bicycle is parked on a side walk."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1091460", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000343325.jpg", "positive_caption": ["a brightly decorated bus sits on the road."], "negative_caption": ["a brightly decorated airplane sits on the road."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1166523", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000480793.jpg", "positive_caption": ["a white toilet sitting next to a shower."], "negative_caption": ["a white bed sitting next to a shower."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1233471", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000466125.jpg", "positive_caption": ["the child smiles brightly while being handed a pink umbrella."], "negative_caption": ["the child smiles brightly while being handed a pink tie."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1047545", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000521472.jpg", "positive_caption": ["a large commercial airplane parked on the runway"], "negative_caption": ["a large commercial truck parked on the runway"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1173921", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000011198.jpg", "positive_caption": ["some plates of salad by a pan of pizza with chicken and broccoli."], "negative_caption": ["some plates of salad by a pan of sandwich with chicken and broccoli."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1208518", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000186147.jpg", "positive_caption": ["a red plate full of meatballs and broccoli on a table"], "negative_caption": ["a red plate full of meatballs and broccoli on a chair"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1154511", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000175151.jpg", "positive_caption": ["a city bus is riding down the empty street."], "negative_caption": ["a city airplane is riding down the empty street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1249407", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000307265.jpg", "positive_caption": ["a dog finds wonderful things to sniff in the oddest places."], "negative_caption": ["a bear finds wonderful things to sniff in the oddest places."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1160814", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000448697.jpg", "positive_caption": ["the big ben clock tower towering over a traffic light."], "negative_caption": ["the big ben book tower towering over a traffic light."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1173872", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000575395.jpg", "positive_caption": ["a person on a court with a tennis racket."], "negative_caption": ["a person on a court with a tennis ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1171615", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000004665.jpg", "positive_caption": ["a just married couple in the back of a car."], "negative_caption": ["a just married couple in the back of a train."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1010037", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000094795.jpg", "positive_caption": ["thirsty black dog sitting by the beach near people with surfboards"], "negative_caption": ["thirsty black bird sitting by the beach near people with surfboards"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1110564", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000307847.jpg", "positive_caption": ["a train is sitting in a train station."], "negative_caption": ["a bus is sitting in a train station."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1234990", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000452027.jpg", "positive_caption": ["three giraffe near some trees in the grass."], "negative_caption": ["three zebra near some trees in the grass."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1204084", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000572899.jpg", "positive_caption": ["two towel shaped elephants on a bed with pillows."], "negative_caption": ["two towel shaped elephants on a table with pillows."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1152774", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000246746.jpg", "positive_caption": ["a horse being ridden in the middle of the grass."], "negative_caption": ["a cow being ridden in the middle of the grass."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1072467", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000488942.jpg", "positive_caption": ["a clock tower is on the corner in front of an office building"], "negative_caption": ["a book tower is on the corner in front of an office building"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1232197", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000292428.jpg", "positive_caption": ["a skateboard being used as a footrest by two tennis shoe clad feet."], "negative_caption": ["a frisbee being used as a footrest by two tennis shoe clad feet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1041630", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000571678.jpg", "positive_caption": ["a very cute teddy bear holding a plaid pillow"], "negative_caption": ["a very cute teddy cat holding a plaid pillow"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1285890", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000544825.jpg", "positive_caption": ["a group of young people stand on a small boat in the water."], "negative_caption": ["a group of young people stand on a small airplane in the water."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1205859", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000330897.jpg", "positive_caption": ["a small pizza sits on a plate in front of a person"], "negative_caption": ["a small sandwich sits on a plate in front of a person"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1050282", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000079966.jpg", "positive_caption": ["a black dog sitting in the basket of a white bicycle."], "negative_caption": ["a black horse sitting in the basket of a white bicycle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1188287", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000210761.jpg", "positive_caption": ["a man reaching into the refrigerator while working on a large meal."], "negative_caption": ["a man reaching into the microwave while working on a large meal."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1022292", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000447043.jpg", "positive_caption": ["we are looking at a clock tower on an old animal."], "negative_caption": ["we are looking at a book tower on an old animal."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1051892", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000281028.jpg", "positive_caption": ["a scene shows the inside of a bus with seats."], "negative_caption": ["a scene shows the inside of a airplane with seats."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1144144", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000292266.jpg", "positive_caption": ["a dog with large ears pokes his nose through a wheel with red spokes."], "negative_caption": ["a horse with large ears pokes his nose through a wheel with red spokes."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1018442", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000209972.jpg", "positive_caption": ["there is a boat that is sitting along side the beach shore"], "negative_caption": ["there is a airplane that is sitting along side the beach shore"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1175524", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000549384.jpg", "positive_caption": ["a neatly arranged bathroom with shower, tub, toilet, and sink"], "negative_caption": ["a neatly arranged bathroom with shower, tub, bed, and sink"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1271081", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000372717.jpg", "positive_caption": ["a smart phone sitting on a table next to a yellow donut."], "negative_caption": ["a smart phone sitting on a bed next to a yellow donut."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1059386", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000271820.jpg", "positive_caption": ["the view of a living room from a bed room."], "negative_caption": ["the view of a living room from a couch room."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1253172", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000437859.jpg", "positive_caption": ["a black car parked in front of parking meter with a building in background."], "negative_caption": ["a black airplane parked in front of parking meter with a building in background."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1212553", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000461408.jpg", "positive_caption": ["a man and a woman open a pizza box."], "negative_caption": ["a man and a woman open a sandwich box."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1112150", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000536038.jpg", "positive_caption": ["the woman is reading something while laying down in bed."], "negative_caption": ["the woman is reading something while laying down in couch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1223658", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000097278.jpg", "positive_caption": ["a woman in blue jacket standing on a snowboard."], "negative_caption": ["a woman in blue jacket standing on a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1041996", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000282878.jpg", "positive_caption": ["a large plateful of cheese pizza is on a tablecloth."], "negative_caption": ["a large plateful of cheese sandwich is on a tablecloth."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1133189", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000037865.jpg", "positive_caption": ["a girl in pink shirt eating a chocolate frosted donut."], "negative_caption": ["a girl in pink shirt eating a chocolate frosted banana."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1162218", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000034418.jpg", "positive_caption": ["a cow that is bent over near the grass."], "negative_caption": ["a elephant that is bent over near the grass."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1220920", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000037109.jpg", "positive_caption": ["a plate topped with a muffin and piece of cake."], "negative_caption": ["a plate topped with a muffin and piece of sandwich."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1127636", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000094746.jpg", "positive_caption": ["there is a man in a suit store talking on the phone"], "negative_caption": ["there is a man in a suit store talking on the laptop"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1254918", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000279769.jpg", "positive_caption": ["a banana resting on a paper towel atop a wooden table."], "negative_caption": ["a banana resting on a paper towel atop a wooden bed."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1109574", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000032391.jpg", "positive_caption": ["a japanese store with a decorative surfboard and japanese sign with palm trees and tropical flowers"], "negative_caption": ["a japanese store with a decorative kite and japanese sign with palm trees and tropical flowers"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1241607", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000541132.jpg", "positive_caption": ["a double long bus makes a turn through an intersection."], "negative_caption": ["a double long bicycle makes a turn through an intersection."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1279905", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000428658.jpg", "positive_caption": ["a small kid holding on to a kite"], "negative_caption": ["a small kid holding on to a frisbee"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1239565", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000110434.jpg", "positive_caption": ["a man wearing a hoodie with a cell phone in an elevator"], "negative_caption": ["a man wearing a hoodie with a cell keyboard in an elevator"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1086078", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000063478.jpg", "positive_caption": ["a toothbrush sitting next to a soap bottle"], "negative_caption": ["a toothbrush sitting next to a soap cup"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1290889", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000273230.jpg", "positive_caption": ["a person on a field catching a frisbee"], "negative_caption": ["a person on a field catching a ball"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1094764", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000481886.jpg", "positive_caption": ["a pizza covered in leafy greens on a table."], "negative_caption": ["a sandwich covered in leafy greens on a table."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1260132", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000254050.jpg", "positive_caption": ["this fluffy dog is loaded up wit some gear."], "negative_caption": ["this fluffy horse is loaded up wit some gear."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1250515", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000034115.jpg", "positive_caption": ["a stuffed bear that is in a train seat."], "negative_caption": ["a stuffed cat that is in a train seat."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1084997", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000368442.jpg", "positive_caption": ["this is a giraffe standing in the middle of grass"], "negative_caption": ["this is a horse standing in the middle of grass"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1053843", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000097434.jpg", "positive_caption": ["a man sits on the sidewalk next to a police motorcycle with a police officer in the background."], "negative_caption": ["a man sits on the sidewalk next to a police car with a police officer in the background."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1000478", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000559614.jpg", "positive_caption": ["a rusty flatbed truck sitting by a building"], "negative_caption": ["a rusty flatbed airplane sitting by a building"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1055024", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000427133.jpg", "positive_caption": ["a woman and dog herding three sheep at a contest."], "negative_caption": ["a woman and horse herding three sheep at a contest."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1181565", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000280424.jpg", "positive_caption": ["a group of zebra in a dirt area by a fence."], "negative_caption": ["a group of giraffe in a dirt area by a fence."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1071995", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000366179.jpg", "positive_caption": ["a public transit bus on a city street"], "negative_caption": ["a public transit motorcycle on a city street"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1242040", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000328596.jpg", "positive_caption": ["a little girl sitting in front of a plate of pizza."], "negative_caption": ["a little girl sitting in front of a plate of broccoli."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1292601", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000124621.jpg", "positive_caption": ["a blue train is going on the tracks by an old building."], "negative_caption": ["a blue truck is going on the tracks by an old building."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1190580", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000221555.jpg", "positive_caption": ["a bearded male tennis player striking a tennis ball."], "negative_caption": ["a bearded male tennis player striking a tennis racket."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1133060", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000317725.jpg", "positive_caption": ["a small bowl with two dessert balls with sprinkles"], "negative_caption": ["a small knife with two dessert balls with sprinkles"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1042156", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000056752.jpg", "positive_caption": ["man on a bicycle riding on the road next to a river."], "negative_caption": ["man on a motorcycle riding on the road next to a river."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1098283", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000028194.jpg", "positive_caption": ["a smiling woman in a wetsuit catches a wave on a surfboard"], "negative_caption": ["a smiling woman in a wetsuit catches a wave on a kite"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1223344", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000044022.jpg", "positive_caption": ["a cat on a bed in a bed room"], "negative_caption": ["a cat on a couch in a bed room"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1152330", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000253819.jpg", "positive_caption": ["a man that is jumping in the air with a skateboard."], "negative_caption": ["a man that is jumping in the air with a frisbee."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1087847", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000440400.jpg", "positive_caption": ["woman standing under clear umbrella on urban sidewalk."], "negative_caption": ["woman standing under clear tie on urban sidewalk."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1063654", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000550013.jpg", "positive_caption": ["man with golf club and a dog and a goat"], "negative_caption": ["man with golf club and a horse and a goat"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1128837", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000357238.jpg", "positive_caption": ["the kite surfer is standing below the flying kite on a beach."], "negative_caption": ["the kite surfer is standing below the flying surfboard on a beach."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1201593", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000242644.jpg", "positive_caption": ["a tall clock tower with a ferris wheel in the background"], "negative_caption": ["a tall book tower with a ferris wheel in the background"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1219489", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000061959.jpg", "positive_caption": ["a transit bus driving down a highway by some fast food restaurants."], "negative_caption": ["a transit motorcycle driving down a highway by some fast food restaurants."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1061470", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000397279.jpg", "positive_caption": ["a person standing on a tennis court with a racket."], "negative_caption": ["a person standing on a tennis court with a ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1268581", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000162627.jpg", "positive_caption": ["a girl that is sitting on a horse."], "negative_caption": ["a girl that is sitting on a cow."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1274477", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000536791.jpg", "positive_caption": ["an image of a boy playing on a skateboard"], "negative_caption": ["an image of a boy playing on a frisbee"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1041538", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000109653.jpg", "positive_caption": ["a kite with two long tail streamers flying in a sky with a single cloud"], "negative_caption": ["a surfboard with two long tail streamers flying in a sky with a single cloud"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1186937", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000534270.jpg", "positive_caption": ["two people in ridiculous looking umbrella hats."], "negative_caption": ["two people in ridiculous looking tie hats."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1213505", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000234679.jpg", "positive_caption": ["a woman wearing an oven mitt taking something out of an oven."], "negative_caption": ["a woman wearing an microwave mitt taking something out of an oven."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1029333", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000414296.jpg", "positive_caption": ["a large metal clock hanging off the side of a tall building."], "negative_caption": ["a large metal scissors hanging off the side of a tall building."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1014043", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000297604.jpg", "positive_caption": ["the man in the river is standing on an elephant."], "negative_caption": ["the man in the river is standing on an horse."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1205975", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000218844.jpg", "positive_caption": ["a counter with a coffee maker and a microwave."], "negative_caption": ["a counter with a coffee maker and a toaster."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1090130", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000205498.jpg", "positive_caption": ["a kitchen table with a vase and flower and window overlooking it."], "negative_caption": ["a kitchen bed with a vase and flower and window overlooking it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1223923", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000471273.jpg", "positive_caption": ["a boy flying a kite in a park."], "negative_caption": ["a boy flying a frisbee in a park."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1089317", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000239537.jpg", "positive_caption": ["a tennis player hitting a ball in a low position."], "negative_caption": ["a tennis player hitting a racket in a low position."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1013970", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000090062.jpg", "positive_caption": ["a cow is standing next to chopped wood looking at the camera."], "negative_caption": ["a dog is standing next to chopped wood looking at the camera."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1228069", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000036761.jpg", "positive_caption": ["a red motorcycle parked in front of a store."], "negative_caption": ["a red bicycle parked in front of a store."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1060579", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000581317.jpg", "positive_caption": ["woman standing in a field of grass trying to use her cell phone."], "negative_caption": ["woman standing in a field of grass trying to use her cell laptop."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1179956", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000573179.jpg", "positive_caption": ["a young boy standing next to a baby horse."], "negative_caption": ["a young boy standing next to a baby cow."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1040803", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000331667.jpg", "positive_caption": ["a silver and red train at a stop with sign reading \"stafford.\""], "negative_caption": ["a silver and red bus at a stop with sign reading \"stafford.\""], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1280841", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000242968.jpg", "positive_caption": ["a vase filled with pens with fake sunflowers attached on a desk that says \"visitors must sign in\"."], "negative_caption": ["a clock filled with pens with fake sunflowers attached on a desk that says \"visitors must sign in\"."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1097913", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000083476.jpg", "positive_caption": ["a cat laying on top of a bed with a remote."], "negative_caption": ["a cat laying on top of a couch with a remote."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1265918", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000439443.jpg", "positive_caption": ["a surfer in black pants and a blue shirt rides a surfboard in the ocean."], "negative_caption": ["a surfer in black pants and a blue shirt rides a kite in the ocean."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1291523", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000574376.jpg", "positive_caption": ["woman in a blue shirt and black shorts kneeling beside a surfboard."], "negative_caption": ["woman in a blue shirt and black shorts kneeling beside a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1200640", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000127496.jpg", "positive_caption": ["top view of a bathroom including tub, sink and toilet."], "negative_caption": ["top view of a bathroom including tub, refrigerator and toilet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1233559", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000013145.jpg", "positive_caption": ["an orange has been sliced in half and is being displayed."], "negative_caption": ["an apple has been sliced in half and is being displayed."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1237310", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000467990.jpg", "positive_caption": ["a train makes its way through the terminal."], "negative_caption": ["a bus makes its way through the terminal."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1190529", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000451077.jpg", "positive_caption": ["two trains, one yellow and one red, travel near a train station"], "negative_caption": ["two trains, one yellow and one red, travel near a bus station"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1281117", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000077345.jpg", "positive_caption": ["a man riding a skateboard down a curvy road."], "negative_caption": ["a man riding a frisbee down a curvy road."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1117926", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000355776.jpg", "positive_caption": ["a young girl brushing her teeth at the sink."], "negative_caption": ["a young girl brushing her teeth at the refrigerator."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1246131", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000131089.jpg", "positive_caption": ["a young child in the yard holding up a bat."], "negative_caption": ["a young child in the yard holding up a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1058870", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000119233.jpg", "positive_caption": ["a cat lying a top on the desk on a laptop."], "negative_caption": ["a cat lying a top on the desk on a tv."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1235075", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000227851.jpg", "positive_caption": ["a woman talks on a cell phone while fanning herself."], "negative_caption": ["a woman talks on a cell laptop while fanning herself."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1194986", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000302380.jpg", "positive_caption": ["man holding up a yellow cake with candles on the top of it."], "negative_caption": ["man holding up a yellow pizza with candles on the top of it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1080673", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000374858.jpg", "positive_caption": ["a man sitting on a bench with a book and a bag."], "negative_caption": ["a man sitting on a bench with a scissors and a bag."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1069094", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000210042.jpg", "positive_caption": ["a zebra standing in the grass near a fence."], "negative_caption": ["a giraffe standing in the grass near a fence."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1146242", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000478474.jpg", "positive_caption": ["a tractor truck truckrying an extra trailer down a street."], "negative_caption": ["a tractor car carrying an extra trailer down a street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1137422", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000310560.jpg", "positive_caption": ["this tower has a flag on its top and a clock in the middle"], "negative_caption": ["this tower has a flag on its top and a book in the middle"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1232219", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000015260.jpg", "positive_caption": ["two-tiered white fondant cake on pedestal with tiers separated by two rows of white and green roses covered with a dark wire wide-mesh birdcage top with a bird perched atop for a handle."], "negative_caption": ["two-tiered white fondant pizza on pedestal with tiers separated by two rows of white and green roses covered with a dark wire wide-mesh birdcage top with a bird perched atop for a handle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1046771", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000002753.jpg", "positive_caption": ["a dog holding a yellow frisbee in it's mouth."], "negative_caption": ["a dog holding a yellow ball in it's mouth."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1168623", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000321242.jpg", "positive_caption": ["a kitchen being remodeled with a microwave"], "negative_caption": ["a kitchen being remodeled with a sink"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1270190", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000209539.jpg", "positive_caption": ["there is an umbrella next to the palm trees."], "negative_caption": ["there is an tie next to the palm trees."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1228674", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000217285.jpg", "positive_caption": ["the man is getting ready to hit the ball in the baseball game."], "negative_caption": ["the man is getting ready to hit the glove in the baseball game."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1006145", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000227986.jpg", "positive_caption": ["a man in a tie stands in a room"], "negative_caption": ["a man in a suitcase stands in a room"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1078534", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000374485.jpg", "positive_caption": ["a vw bus vehicle is sitting curbside on the street."], "negative_caption": ["a vw motorcycle vehicle is sitting curbside on the street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1234804", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000441861.jpg", "positive_caption": ["a soccer catcher behind the fence is trying to catch the ball."], "negative_caption": ["a soccer catcher behind the fence is trying to catch the glove."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1245585", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000460646.jpg", "positive_caption": ["a bus sitting on the side of a road."], "negative_caption": ["a motorcycle sitting on the side of a road."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1046711", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000028359.jpg", "positive_caption": ["a small white dog's reflection on a car's side view mirror."], "negative_caption": ["a small white horse's reflection on a car's side view mirror."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1048410", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000238836.jpg", "positive_caption": ["a car is stopped at a red light"], "negative_caption": ["a bicycle is stopped at a red light"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1166091", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000088507.jpg", "positive_caption": ["downhill skier with orange helmet and backpack airborne while skiing down the slope."], "negative_caption": ["downhill skier with apple helmet and backpack airborne while skiing down the slope."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1124288", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000058816.jpg", "positive_caption": ["a bath room with a toilet a stool and handle bars"], "negative_caption": ["a bath room with a bed a stool and handle bars"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1271314", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000092801.jpg", "positive_caption": ["a fluffy cat laying down in a suitcase."], "negative_caption": ["a fluffy dog laying down in a suitcase."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1220525", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000130645.jpg", "positive_caption": ["a dirty bus goes down the highway in front of other cars."], "negative_caption": ["a dirty airplane goes down the highway in front of other cars."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1294873", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000229599.jpg", "positive_caption": ["there is a glass bowl with oranges in it."], "negative_caption": ["there is a fork bowl with oranges in it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1008025", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000179112.jpg", "positive_caption": ["a woman holding a smart phone in a room."], "negative_caption": ["a woman holding a smart laptop in a room."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1232385", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000115721.jpg", "positive_caption": ["a dog with its eyes closed on a cushion."], "negative_caption": ["a horse with its eyes closed on a cushion."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1063881", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000062251.jpg", "positive_caption": ["firefighters are riding in the back of a fire truck."], "negative_caption": ["firefighters are riding in the back of a fire car."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1135282", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000177015.jpg", "positive_caption": ["a cat sitting on the man's lap while the man types on the laptop."], "negative_caption": ["a dog sitting on the man's lap while the man types on the laptop."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1010183", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000308394.jpg", "positive_caption": ["an older woman riding a train while sitting under it's window."], "negative_caption": ["an older woman riding a bus while sitting under it's window."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1001429", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000029906.jpg", "positive_caption": ["a broccoli plant growing inside of a fenced garden."], "negative_caption": ["a banana plant growing inside of a fenced garden."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1102495", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000296236.jpg", "positive_caption": ["a person leaning on a glass looking at doughnuts being made"], "negative_caption": ["a person leaning on a cup looking at doughnuts being made"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1027236", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000535933.jpg", "positive_caption": ["a plain pizza is shown on a wooden table with empty plates."], "negative_caption": ["a plain sandwich is shown on a wooden table with empty plates."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1040906", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000484604.jpg", "positive_caption": ["a pizza is covered with toppings to resemble an angry bird."], "negative_caption": ["a pizza is covered with toppings to resemble an angry dog."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1069213", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000553353.jpg", "positive_caption": ["a man drinking in a suit and tie."], "negative_caption": ["a man drinking in a suit and suitcase."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1130264", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000066191.jpg", "positive_caption": ["a basebat player on the field with a bat."], "negative_caption": ["a baseball player on the field with a ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1231836", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000436323.jpg", "positive_caption": ["a couple of young men playing a game of frisbee."], "negative_caption": ["a couple of young men playing a game of ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1153970", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000501142.jpg", "positive_caption": ["a cow in a shallow lake stares at a canoe."], "negative_caption": ["a dog in a shallow lake stares at a canoe."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1085453", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000135497.jpg", "positive_caption": ["a man sits at a table and he is holding two fingers up on each hand."], "negative_caption": ["a man sits at a bed and he is holding two fingers up on each hand."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1065544", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000279838.jpg", "positive_caption": ["the woman using a cell phone touches her long hair."], "negative_caption": ["the woman using a cell laptop touches her long hair."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1277333", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000202040.jpg", "positive_caption": ["one black motorcycle and one red motorcycle next to each other"], "negative_caption": ["one black motorcycle and one red car next to each other"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1218804", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000304578.jpg", "positive_caption": ["a young woman sitting in a field next to a cow."], "negative_caption": ["a young woman sitting in a field next to a dog."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1288812", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000540820.jpg", "positive_caption": ["two wash basins side-by-side next to a toilet and a bidet."], "negative_caption": ["two wash basins side-by-side next to a bed and a bidet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1037809", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000222467.jpg", "positive_caption": ["a cat laying on top of a tv with its paws stretched out on it."], "negative_caption": ["a giraffe laying on top of a tv with its paws stretched out on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1160105", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000527906.jpg", "positive_caption": ["a english muffin sandwich has a single bit in it."], "negative_caption": ["a english muffin pizza has a single bit in it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1127383", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000416188.jpg", "positive_caption": ["a man in a tuxedo sits at a table and uses a laptop"], "negative_caption": ["a man in a tuxedo sits at a bed and uses a laptop"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1097543", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000001164.jpg", "positive_caption": ["two girls bathe an elephant lying on its side."], "negative_caption": ["two girls bathe an horse lying on its side."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1213371", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000430750.jpg", "positive_caption": ["people walking toward an airplane to board it."], "negative_caption": ["people walking toward an truck to board it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1196675", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000136250.jpg", "positive_caption": ["a cat is standing on a board game"], "negative_caption": ["a dog is standing on a board game"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1175112", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000195367.jpg", "positive_caption": ["a cow with a black face is in a field"], "negative_caption": ["a dog with a black face is in a field"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1160007", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000472080.jpg", "positive_caption": ["a desk with a laptop and a mouse and a mouse"], "negative_caption": ["a desk with a laptop and a keyboard and a keyboard"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1096515", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000332532.jpg", "positive_caption": ["a white toilet siting in a bathroom next to as ink."], "negative_caption": ["a white bed siting in a bathroom next to as ink."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1263501", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000290951.jpg", "positive_caption": ["a pair of women walking through a lobby with several large umbrella's in the ceiling."], "negative_caption": ["a pair of women walking through a lobby with several large tie's in the ceiling."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1108795", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000082396.jpg", "positive_caption": ["a statue of a person riding a horse"], "negative_caption": ["a statue of a person riding a cow"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1274639", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000356478.jpg", "positive_caption": ["a baby elephant is walking in the dirt."], "negative_caption": ["a baby horse is walking in the dirt."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1017898", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000354507.jpg", "positive_caption": ["a close up of a brown tie with white polka dots"], "negative_caption": ["a close up of a brown suitcase with white polka dots"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1108282", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000200143.jpg", "positive_caption": ["a family of zebra are eating grass at the same time."], "negative_caption": ["a family of giraffe are eating grass at the same time."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1026255", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000033377.jpg", "positive_caption": ["a woman and a man holding a yellow surfboard with two dogs on it."], "negative_caption": ["a woman and a man holding a yellow frisbee with two dogs on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1221534", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000476664.jpg", "positive_caption": ["a cat laying on a bed on the ground"], "negative_caption": ["a cat laying on a couch on the ground"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1272947", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000513189.jpg", "positive_caption": ["a man is riding on a surfboard at the beach"], "negative_caption": ["a man is riding on a kite at the beach"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1042270", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000379488.jpg", "positive_caption": ["a person riding a wave on top of a surfboard."], "negative_caption": ["a person riding a wave on top of a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1035042", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000038574.jpg", "positive_caption": ["there is a black hat and white glove with birthday greetings."], "negative_caption": ["there is a black hat and white surfboard with birthday greetings."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1288193", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000194313.jpg", "positive_caption": ["a black cat laying on a bathroom sink."], "negative_caption": ["a black dog laying on a bathroom sink."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1241100", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000244931.jpg", "positive_caption": ["man sitting down on a snow trail with his snowboard on his feet."], "negative_caption": ["man sitting down on a snow trail with his kite on his feet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1207648", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000010324.jpg", "positive_caption": ["a close up of a refrigerator with one door open"], "negative_caption": ["a close up of a microwave with one door open"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1153687", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000299355.jpg", "positive_caption": ["a meal of broccoli, meat, and sauce on a plate."], "negative_caption": ["a meal of carrot, meat, and sauce on a plate."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1193048", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000014880.jpg", "positive_caption": ["a red stop sign that is on the side of a bus."], "negative_caption": ["a red stop sign that is on the side of a bicycle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1077769", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000517515.jpg", "positive_caption": ["a table topped with hot dogs and fries."], "negative_caption": ["a bed topped with hot dogs and fries."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1154935", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000434129.jpg", "positive_caption": ["elaborate toronto blue jays professional baseball cap cake"], "negative_caption": ["elaborate toronto blue jays professional baseball cap sandwich"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1017136", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000335844.jpg", "positive_caption": ["the portable oven has a small pizza cooking in it."], "negative_caption": ["the portable microwave has a small pizza cooking in it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1199571", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000472078.jpg", "positive_caption": ["two people wearing skis on a snowy hill"], "negative_caption": ["two people wearing snowboard on a snowy hill"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1075809", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000445298.jpg", "positive_caption": ["a cow grazing upon a hill on a foggy day"], "negative_caption": ["a elephant grazing upon a hill on a foggy day"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1085689", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000565233.jpg", "positive_caption": ["man sitting on his bed while using his laptop."], "negative_caption": ["man sitting on his couch while using his laptop."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1036841", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000172079.jpg", "positive_caption": ["a large vase next two to a other smaller vases."], "negative_caption": ["a large clock next two to a other smaller vases."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1146907", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000366576.jpg", "positive_caption": ["a zebra grazes in a cage at a fair."], "negative_caption": ["a horse grazes in a cage at a fair."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1221807", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000537438.jpg", "positive_caption": ["a cut piece of cake that is sitting on a plate."], "negative_caption": ["a cut piece of pizza that is sitting on a plate."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1244620", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000503294.jpg", "positive_caption": ["a large living room with a cat on the rug"], "negative_caption": ["a large living room with a dog on the rug"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1148235", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000006028.jpg", "positive_caption": ["a man riding a wave on top of a surfboard."], "negative_caption": ["a man riding a wave on top of a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1042273", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000025990.jpg", "positive_caption": ["a child with a cap, sitting in a garden holding a bat in one hand and a flower in other."], "negative_caption": ["a child with a cap, sitting in a garden holding a racket in one hand and a flower in other."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1077585", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000214184.jpg", "positive_caption": ["a cat lays down on a row of books"], "negative_caption": ["a dog lays down on a row of books"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1241452", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000392933.jpg", "positive_caption": ["a giraffe is standing on a pile of logs in a grassy field next to trees."], "negative_caption": ["a bird is standing on a pile of logs in a grassy field next to trees."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1150583", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000413395.jpg", "positive_caption": ["a man resting on a couch with two different colored cats."], "negative_caption": ["a man resting on a bed with two different colored cats."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1078097", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000457348.jpg", "positive_caption": ["a bus driving down a street past traffic lights."], "negative_caption": ["a bicycle driving down a street past traffic lights."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1061597", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000123642.jpg", "positive_caption": ["a steak sandwich on a plate with a unique food design on it."], "negative_caption": ["a steak pizza on a plate with a unique food design on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1012259", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000161873.jpg", "positive_caption": ["a giraffe is walking on a roadway with cars on it."], "negative_caption": ["a zebra is walking on a roadway with cars on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1174324", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000037119.jpg", "positive_caption": ["multiple black and white cows standing in a cow pen."], "negative_caption": ["multiple black and white cows standing in a giraffe pen."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1167783", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000470521.jpg", "positive_caption": ["a gray cat on top of a black purse."], "negative_caption": ["a gray dog on top of a black purse."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1159773", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000514271.jpg", "positive_caption": ["archways in a brick building below a clock tower."], "negative_caption": ["archways in a brick building below a book tower."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1127300", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000005586.jpg", "positive_caption": ["a man playing tennis hits a ball across the court"], "negative_caption": ["a man playing tennis hits a racket across the court"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1171583", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000561357.jpg", "positive_caption": ["a close up of a plate with a burger and a hot dog"], "negative_caption": ["a close up of a plate with a burger and a hot horse"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1132230", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000098029.jpg", "positive_caption": ["several objects displayed on a kitchen table including bread, oranges and plating."], "negative_caption": ["several objects displayed on a kitchen bed including bread, oranges and plating."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1232666", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000001561.jpg", "positive_caption": ["a very small bird sitting on a skateboard."], "negative_caption": ["a very small dog sitting on a skateboard."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1272163", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000311180.jpg", "positive_caption": ["hand holding a small pair of scissors with a green handle."], "negative_caption": ["hand holding a small pair of vase with a green handle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1037338", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000528351.jpg", "positive_caption": ["a car sitting in the middle of the grass in the rain."], "negative_caption": ["a train sitting in the middle of the grass in the rain."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1241291", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000493610.jpg", "positive_caption": ["a large group of people crammed into and on top of a truck."], "negative_caption": ["a large group of people crammed into and on top of a car."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1286392", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000200959.jpg", "positive_caption": ["person on snowboard jumping in air with mountains in the background."], "negative_caption": ["person on kite jumping in air with mountains in the background."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1283686", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000370270.jpg", "positive_caption": ["a person hitting a ball with a stick in a office."], "negative_caption": ["a person hitting a skateboard with a stick in a office."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1164041", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000241149.jpg", "positive_caption": ["a white plate topped with a pie and a bowl of butter."], "negative_caption": ["a white plate topped with a pie and a glass of butter."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1225551", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000430467.jpg", "positive_caption": ["a bus driving down a street past tall buildings."], "negative_caption": ["a bicycle driving down a street past tall buildings."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1249421", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000224861.jpg", "positive_caption": ["the cat is laying on the clothes in the suitcase."], "negative_caption": ["the dog is laying on the clothes in the suitcase."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1001909", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000448837.jpg", "positive_caption": ["a man laying in a bed with food in his mouth."], "negative_caption": ["a man laying in a couch with food in his mouth."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1291264", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000149912.jpg", "positive_caption": ["a guy wearing a straw hat and a gray hoodie milks a cow."], "negative_caption": ["a guy wearing a straw hat and a gray hoodie milks a giraffe."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1233361", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000557732.jpg", "positive_caption": ["young person on snowboard going down gentle slope."], "negative_caption": ["young person on kite going down gentle slope."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1260041", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000316189.jpg", "positive_caption": ["a catcher throws the ball during a baseball game"], "negative_caption": ["a catcher throws the glove during a baseball game"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1199322", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000402778.jpg", "positive_caption": ["a brown dog running with a yellow frisbee in it's mouth."], "negative_caption": ["a brown bear running with a yellow frisbee in it's mouth."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1032368", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000547744.jpg", "positive_caption": ["a commercial bus is stopped in front of a building."], "negative_caption": ["a commercial airplane is stopped in front of a building."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1256973", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000572210.jpg", "positive_caption": ["a little girl holding a cell phone in her hands."], "negative_caption": ["a little girl holding a cell laptop in her hands."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1066946", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000572462.jpg", "positive_caption": ["a collage is shown of a train ride and stop."], "negative_caption": ["a collage is shown of a bus ride and stop."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1144408", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000291686.jpg", "positive_caption": ["the young man holds his fork before a meal."], "negative_caption": ["the young man holds his glass before a meal."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1255400", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000261563.jpg", "positive_caption": ["a brown dog and a black dog play with a yellow frisbee in a field."], "negative_caption": ["a brown dog and a black dog play with a yellow ball in a field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1213539", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000055545.jpg", "positive_caption": ["a blue and white train on tracks near buildings."], "negative_caption": ["a blue and white bus on tracks near buildings."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1062336", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000286760.jpg", "positive_caption": ["a cake with frosting sitting on a pedestal."], "negative_caption": ["a sandwich with frosting sitting on a pedestal."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1050076", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000105974.jpg", "positive_caption": ["a man leaping in the air to grab a frisbee."], "negative_caption": ["a man leaping in the air to grab a ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1101478", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000298680.jpg", "positive_caption": ["a bowl full of a certain fruit with a utensil in it."], "negative_caption": ["a knife full of a certain fruit with a utensil in it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1027025", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000084680.jpg", "positive_caption": ["a close up of a person in costume operating a microwave"], "negative_caption": ["a close up of a person in costume operating a toaster"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1172078", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000270571.jpg", "positive_caption": ["a woman holding a large knife and a piece of food."], "negative_caption": ["a woman holding a large bottle and a piece of food."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1193002", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000497660.jpg", "positive_caption": ["a parked truck and trailer with a large load."], "negative_caption": ["a parked motorcycle and trailer with a large load."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1250422", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000160437.jpg", "positive_caption": ["a zebra laying next to another zebra on a dirt covered floor."], "negative_caption": ["a cat laying next to another zebra on a dirt covered floor."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1229327", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000425475.jpg", "positive_caption": ["a woman's hand holding a glass of wine."], "negative_caption": ["a woman's hand holding a spoon of wine."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1029896", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000537513.jpg", "positive_caption": ["the room has two bed and a chair."], "negative_caption": ["the room has two bed and a couch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1170560", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000279549.jpg", "positive_caption": ["a tennis player has hit a ball back to his opponent."], "negative_caption": ["a tennis player has hit a racket back to his opponent."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1284511", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000422200.jpg", "positive_caption": ["man sitting on the sidewalk talking on a phone."], "negative_caption": ["man sitting on the sidewalk talking on a laptop."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1075283", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000041373.jpg", "positive_caption": ["a white cat with black spots is curled up on a bed."], "negative_caption": ["a white cat with black spots is curled up on a table."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1103719", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000082740.jpg", "positive_caption": ["a black and white photo of a person jumping on a horse."], "negative_caption": ["a black and white photo of a person jumping on a cow."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1072153", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000242452.jpg", "positive_caption": ["a young baseball player is at base about to hit the ball"], "negative_caption": ["a young baseball player is at base about to hit the glove"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1269427", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000426878.jpg", "positive_caption": ["a woman holds a little girl who stands on top of a skateboard."], "negative_caption": ["a woman holds a little girl who stands on top of a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1200047", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000028192.jpg", "positive_caption": ["a person flies a kite along a cloudy beach on a clear day."], "negative_caption": ["a person flies a surfboard along a cloudy beach on a clear day."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1013751", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000428064.jpg", "positive_caption": ["a young woman flying a rainbow colored kite."], "negative_caption": ["a young woman flying a rainbow colored frisbee."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1066263", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000187235.jpg", "positive_caption": ["a boat in the water off the shore with a sailboat in the distance"], "negative_caption": ["a airplane in the water off the shore with a sailboat in the distance"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1145038", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000206550.jpg", "positive_caption": ["there is a clock on the spire above the church."], "negative_caption": ["there is a scissors on the spire above the church."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1120189", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000529649.jpg", "positive_caption": ["a cat standing next to an open laptop computer."], "negative_caption": ["a dog standing next to an open laptop computer."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1152651", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000374333.jpg", "positive_caption": ["two laptop computers are on a brown desk."], "negative_caption": ["two tv computers are on a brown desk."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1292806", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000076460.jpg", "positive_caption": ["two adult elephants and one child elephant grazing on grass."], "negative_caption": ["two adult elephants and one child zebra grazing on grass."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1002743", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000057545.jpg", "positive_caption": ["a man in uniform with a cell phone up to his ear."], "negative_caption": ["a man in uniform with a cell laptop up to his ear."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1006634", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000170278.jpg", "positive_caption": ["a dog sleeps on a bed with some blankets."], "negative_caption": ["a dog sleeps on a couch with some blankets."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1176514", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000277694.jpg", "positive_caption": ["a cow that is sitting on the ground in front of a motorcycle."], "negative_caption": ["a cow that is sitting on the ground in front of a car."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1152334", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000034234.jpg", "positive_caption": ["a man with a hat on backwards stands with a skateboard."], "negative_caption": ["a man with a hat on backwards stands with a bat."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1049238", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000254379.jpg", "positive_caption": ["a person holding a remote in their hand."], "negative_caption": ["a person holding a laptop in their hand."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1268934", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000125815.jpg", "positive_caption": ["a train sits parked at a train depot"], "negative_caption": ["a bus sits parked at a train depot"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1264906", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000372495.jpg", "positive_caption": ["an odd bathroom with stone walls, and two rolls of toilet paper"], "negative_caption": ["an odd bathroom with stone walls, and two rolls of bed paper"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1023232", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000093806.jpg", "positive_caption": ["a group of people on skis skiing down a mountain"], "negative_caption": ["a group of people on snowboard skiing down a mountain"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1109633", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000041875.jpg", "positive_caption": ["a young boy in the middle of his bite of pizza"], "negative_caption": ["a young boy in the middle of his bite of banana"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1140475", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000161983.jpg", "positive_caption": ["inside of a bathroom with a sink and mirror."], "negative_caption": ["inside of a bathroom with a refrigerator and mirror."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1195934", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000299254.jpg", "positive_caption": ["a man posing for a picture with a snowboard atop a snowy mountain."], "negative_caption": ["a man posing for a picture with a bat atop a snowy mountain."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1154983", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000384089.jpg", "positive_caption": ["a sexy young woman laying on top of a bed."], "negative_caption": ["a sexy young woman laying on top of a couch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1035011", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000279692.jpg", "positive_caption": ["a kitchen has a microwave sitting in the corner."], "negative_caption": ["a kitchen has a sink sitting in the corner."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1246444", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000031471.jpg", "positive_caption": ["a woman that is standing next to a cow."], "negative_caption": ["a woman that is standing next to a dog."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1182927", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000561979.jpg", "positive_caption": ["a dog sits on the beach between two large boats."], "negative_caption": ["a bird sits on the beach between two large boats."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1160595", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000366576.jpg", "positive_caption": ["a zebra eating grass in an enclosure at a fair."], "negative_caption": ["a horse eating grass in an enclosure at a fair."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1221810", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000113113.jpg", "positive_caption": ["a bowl that has different fruits and vegetables in it."], "negative_caption": ["a knife that has different fruits and vegetables in it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1102226", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000530875.jpg", "positive_caption": ["a man riding a skateboard down the side of a rail."], "negative_caption": ["a man riding a frisbee down the side of a rail."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1291089", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000002592.jpg", "positive_caption": ["a close up of a knife and a cup on a surface"], "negative_caption": ["a close up of a knife and a glass on a surface"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1263100", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000415016.jpg", "positive_caption": ["a little boy swinging a grey basebat bat."], "negative_caption": ["a little boy swinging a grey baseball ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1285200", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000395531.jpg", "positive_caption": ["a stuffed panda bear sitting next to a buddha statue."], "negative_caption": ["a stuffed panda cat sitting next to a buddha statue."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1075681", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000570834.jpg", "positive_caption": ["a white and silver subway train filled with several bicycles"], "negative_caption": ["a white and silver subway truck filled with several bicycles"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1180902", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000420710.jpg", "positive_caption": ["a bus passes over a bridge, under an arch."], "negative_caption": ["a airplane passes over a bridge, under an arch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1190434", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000277383.jpg", "positive_caption": ["several people are playing frisbee in a park."], "negative_caption": ["several people are playing ball in a park."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1116567", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000121876.jpg", "positive_caption": ["a polar bear stands over an orange disc in his enclosure."], "negative_caption": ["a polar bear stands over an carrot disc in his enclosure."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1032645", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000223426.jpg", "positive_caption": ["a open refrigerator filled with food in a room."], "negative_caption": ["a open microwave filled with food in a room."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1180065", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000318721.jpg", "positive_caption": ["a large polar bear swimming in an exhibit at a zoo."], "negative_caption": ["a large polar bird swimming in an exhibit at a zoo."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1033161", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000401614.jpg", "positive_caption": ["a black and white cat sticking it's head inside of a toilet."], "negative_caption": ["a black and white dog sticking it's head inside of a toilet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1052807", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000016228.jpg", "positive_caption": ["a horse pulling a wagon with a conductor down the road."], "negative_caption": ["a cow pulling a wagon with a conductor down the road."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1003586", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000388599.jpg", "positive_caption": ["a white and brown dog pulling frisbee from a hand."], "negative_caption": ["a white and brown dog pulling racket from a hand."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1101084", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000487338.jpg", "positive_caption": ["a person sits at a white table holding a white piece of paper in front of her face and in the background, a man with glass is sitting with his head leaning in his hand."], "negative_caption": ["a person sits at a white table holding a white piece of paper in front of her face and in the background, a man with fork is sitting with his head leaning in his hand."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1022871", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000042793.jpg", "positive_caption": ["lounge beach chairs near umbrella on sand at sunset."], "negative_caption": ["lounge beach chairs near backpack on sand at sunset."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1055493", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000133667.jpg", "positive_caption": ["a little boy sitting in a car shaped bed in a racing themed bedroom."], "negative_caption": ["a little boy sitting in a train shaped bed in a racing themed bedroom."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1260706", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000392981.jpg", "positive_caption": ["a tennis player swinging a racket on a court"], "negative_caption": ["a tennis player swinging a ball on a court"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1133513", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000171181.jpg", "positive_caption": ["table settings for a fancy dinner in a restaurant."], "negative_caption": ["bed settings for a fancy dinner in a restaurant."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1200543", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000056158.jpg", "positive_caption": ["a gray cat is laying on a pink duster."], "negative_caption": ["a gray elephant is laying on a pink duster."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1295445", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000409156.jpg", "positive_caption": ["an asian woman is getting out of a tan color suitcase."], "negative_caption": ["an asian woman is getting out of a tan color umbrella."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1228750", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000145312.jpg", "positive_caption": ["a dog catches a firsbee in the middle of the air."], "negative_caption": ["a bird catches a firsbee in the middle of the air."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1094699", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000178361.jpg", "positive_caption": ["an adult polar bear is swimming in the icy water"], "negative_caption": ["an adult polar bird is swimming in the icy water"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1032528", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000452300.jpg", "positive_caption": ["a dog laying on a rug under a chair."], "negative_caption": ["a dog laying on a rug under a table."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1160985", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000247014.jpg", "positive_caption": ["three different shots show a man with a basebat bat making hand signals."], "negative_caption": ["three different shots show a man with a baseball ball making hand signals."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1097325", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000389622.jpg", "positive_caption": ["a wind up clock with key in a display case."], "negative_caption": ["a wind up scissors with key in a display case."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1014680", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000256003.jpg", "positive_caption": ["there is a toy train in a miniature train set."], "negative_caption": ["there is a toy truck in a miniature train set."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1288246", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000120648.jpg", "positive_caption": ["a hotel bedroom with luggage placed near the bed."], "negative_caption": ["a hotel bedroom with luggage placed near the couch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1088498", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000357238.jpg", "positive_caption": ["a kite being flown in the middle of a beach."], "negative_caption": ["a frisbee being flown in the middle of a beach."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1201581", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000052312.jpg", "positive_caption": ["a man wearing a toothbrush for a moustache."], "negative_caption": ["a man wearing a clock for a moustache."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1035683", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000321223.jpg", "positive_caption": ["a man getting something inside the refrigerator"], "negative_caption": ["a man getting something inside the microwave"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1112724", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000105658.jpg", "positive_caption": ["a bottle of tequila sitting next to an orange cat."], "negative_caption": ["a cup of tequila sitting next to an orange cat."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1144576", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000539888.jpg", "positive_caption": ["man with injured arm sitting on unmade bed looking at something in his hands."], "negative_caption": ["man with injured arm sitting on unmade couch looking at something in his hands."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1088712", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000095022.jpg", "positive_caption": ["a bird with red eyes perched on top of a tree branch."], "negative_caption": ["a sheep with red eyes perched on top of a tree branch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1001312", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000227031.jpg", "positive_caption": ["a man and woman slicing a cake while children watch."], "negative_caption": ["a man and woman slicing a pizza while children watch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1238634", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000319865.jpg", "positive_caption": ["a cat is sleeping in a suitcase with folded clothing"], "negative_caption": ["a dog is sleeping in a suitcase with folded clothing"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1001941", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000311690.jpg", "positive_caption": ["an up close image of a broccoli dish on a plate next to a glass of white wine and a bottle."], "negative_caption": ["an up close image of a broccoli dish on a plate next to a spoon of white wine and a bottle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1049185", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000330974.jpg", "positive_caption": ["a b=very large robust giraffe eating leaves from trees"], "negative_caption": ["a b=very large robust zebra eating leaves from trees"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1197067", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000442301.jpg", "positive_caption": ["a person holding a carrot with other pieces of carrot growing from it."], "negative_caption": ["a person holding a sandwich with other pieces of carrot growing from it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1259739", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000176034.jpg", "positive_caption": ["a clock on a wall with two doors"], "negative_caption": ["a scissors on a wall with two doors"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1023732", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000030066.jpg", "positive_caption": ["a girl with a hat flying a kite on an open range"], "negative_caption": ["a girl with a hat flying a frisbee on an open range"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1231680", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000440043.jpg", "positive_caption": ["a red double decker bus sitting on top of a parking lot."], "negative_caption": ["a red double decker airplane sitting on top of a parking lot."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1174308", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000191096.jpg", "positive_caption": ["the batter's waiting to see if the ball is fair or foul."], "negative_caption": ["the batter's waiting to see if the glove is fair or foul."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1006021", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000529539.jpg", "positive_caption": ["a boy hits a tennis ball to another tennis player."], "negative_caption": ["a boy hits a tennis racket to another tennis player."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1187222", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000245431.jpg", "positive_caption": ["a single bird that sits on a mossy and rocky outcrop."], "negative_caption": ["a single dog that sits on a mossy and rocky outcrop."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1024731", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000547601.jpg", "positive_caption": ["a majolica vase decorated with a fish and filled with wild flowers."], "negative_caption": ["a majolica clock decorated with a fish and filled with wild flowers."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1090622", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000465093.jpg", "positive_caption": ["a cat is standing up scratching the door."], "negative_caption": ["a dog is standing up scratching the door."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1085703", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000217329.jpg", "positive_caption": ["two smiling men prepare hot dog rolls in a kitchen."], "negative_caption": ["two smiling men prepare hot bear rolls in a kitchen."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1019785", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000291606.jpg", "positive_caption": ["a woman standing outside of a metallic bus parked."], "negative_caption": ["a woman standing outside of a metallic airplane parked."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1082974", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000473110.jpg", "positive_caption": ["the cargo train is headed to the next destination."], "negative_caption": ["the cargo bus is headed to the next destination."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1077863", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000015954.jpg", "positive_caption": ["a couple of giraffe standing next to a tree."], "negative_caption": ["a couple of horse standing next to a tree."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1098940", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000002149.jpg", "positive_caption": ["a large white bowl of many green apples."], "negative_caption": ["a large white glass of many green apples."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1226235", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000015303.jpg", "positive_caption": ["a man on a surfboard surfing the waves"], "negative_caption": ["a man on a snowboard surfing the waves"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1170524", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000202343.jpg", "positive_caption": ["a man holding a cell phone at a counter with phones for sale."], "negative_caption": ["a man holding a cell laptop at a counter with phones for sale."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1105193", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000354662.jpg", "positive_caption": ["a bathroom has a toilet and a scale."], "negative_caption": ["a bathroom has a bed and a scale."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1226154", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000463605.jpg", "positive_caption": ["a train with graffiti on the side on it."], "negative_caption": ["a truck with graffiti on the side on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1099548", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000327617.jpg", "positive_caption": ["a vintage photo of a woman with a tennis racket"], "negative_caption": ["a vintage photo of a woman with a tennis glove"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1194292", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000184485.jpg", "positive_caption": ["a brown teddy bear standing next to a tooth brush."], "negative_caption": ["a brown teddy cat standing next to a tooth brush."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1258369", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000181747.jpg", "positive_caption": ["close up of sandwich on plate with coffee mug"], "negative_caption": ["close up of pizza on plate with coffee mug"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1291516", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000355424.jpg", "positive_caption": ["the table has a hawaiian pizza is sitting on it."], "negative_caption": ["the bed has a hawaiian pizza is sitting on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1035481", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000475238.jpg", "positive_caption": ["a train on the tracks at a railroad crossing."], "negative_caption": ["a truck on the tracks at a railroad crossing."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1009169", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000008787.jpg", "positive_caption": ["a man is holidng a dog on teh side walk"], "negative_caption": ["a man is holidng a horse on teh side walk"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1078770", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000165419.jpg", "positive_caption": ["a man that is standing in the sand playing frisbee."], "negative_caption": ["a man that is standing in the sand playing ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1101311", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000526425.jpg", "positive_caption": ["a brown and black dog holding a frisbee in it's mouth."], "negative_caption": ["a brown and black bear holding a frisbee in it's mouth."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1206091", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000282365.jpg", "positive_caption": ["a mother and baby elephant in a green, flowery scene."], "negative_caption": ["a mother and baby zebra in a green, flowery scene."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1160324", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000115178.jpg", "positive_caption": ["a red and black airplane in a clear blue sky upside down."], "negative_caption": ["a red and black truck in a clear blue sky upside down."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1008155", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000163600.jpg", "positive_caption": ["a man holding a toothbrush with a heart on it"], "negative_caption": ["a man holding a clock with a heart on it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1246139", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000214349.jpg", "positive_caption": ["a social gathering with lots of food at the table, including pizza"], "negative_caption": ["a social gathering with lots of food at the chair, including pizza"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1187185", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000108531.jpg", "positive_caption": ["a close up of a motorcycle mirror"], "negative_caption": ["a close up of a car mirror"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1128508", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000564851.jpg", "positive_caption": ["a view of a bunch of trash with a toilet next to it."], "negative_caption": ["a view of a bunch of trash with a bed next to it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1271269", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000377626.jpg", "positive_caption": ["a clock on top of a building with cars parked outside."], "negative_caption": ["a book on top of a building with cars parked outside."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1105422", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000230987.jpg", "positive_caption": ["a cluttered desk with a black chair next to it."], "negative_caption": ["a cluttered desk with a black table next to it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1276227", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000113045.jpg", "positive_caption": ["a wooden spatula in a bowl with shredded carrot."], "negative_caption": ["a wooden spatula in a bowl with shredded broccoli."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1244903", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000352127.jpg", "positive_caption": ["a side of a delivery truck with a picture of people in chefs outfits."], "negative_caption": ["a side of a delivery car with a picture of people in chefs outfits."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1114450", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000301950.jpg", "positive_caption": ["a sandwich with bites and french fries are on a plate."], "negative_caption": ["a pizza with bites and french fries are on a plate."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1110455", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000096251.jpg", "positive_caption": ["three white roses are in a clear vase of water."], "negative_caption": ["three white roses are in a clear clock of water."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1217789", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000053503.jpg", "positive_caption": ["a vase of fresh carnations on a plate on a table top"], "negative_caption": ["a toothbrush of fresh carnations on a plate on a table top"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1277183", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000243418.jpg", "positive_caption": ["people riding bikes followed by a man riding an elephant."], "negative_caption": ["people riding bikes followed by a man riding an horse."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1086362", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000360447.jpg", "positive_caption": ["a man holds a baseball bat near a fence"], "negative_caption": ["a man holds a baseball racket near a fence"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1013879", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000343059.jpg", "positive_caption": ["a green school bus drives down the road with bikes on top."], "negative_caption": ["a green school airplane drives down the road with bikes on top."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1031101", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000039480.jpg", "positive_caption": ["lady on tennis court wearing red tennis outfit and holding racket."], "negative_caption": ["lady on tennis court wearing red tennis outfit and holding ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1215830", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000332625.jpg", "positive_caption": ["an older man sitting on an airplane with earphones and watching a television in the headrest that is in front of his seat."], "negative_caption": ["an older man sitting on an boat with earphones and watching a television in the headrest that is in front of his seat."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1135859", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000249347.jpg", "positive_caption": ["a child in blue shirt playing with a kite in field."], "negative_caption": ["a child in blue shirt playing with a frisbee in field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1021408", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000005816.jpg", "positive_caption": ["a bedroom has a lamp by each side of the bed."], "negative_caption": ["a bedroom has a lamp by each side of the couch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1297085", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000527691.jpg", "positive_caption": ["a woman next to a couch with clothes and a suit case."], "negative_caption": ["a woman next to a bed with clothes and a suit case."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1108581", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000510877.jpg", "positive_caption": ["a gray horse grazing in a field on a sunny day."], "negative_caption": ["a gray cow grazing in a field on a sunny day."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1011134", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000157261.jpg", "positive_caption": ["a green locomotive parked at a train station"], "negative_caption": ["a green locomotive parked at a bus station"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1264885", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000267515.jpg", "positive_caption": ["a tube of toothpaste and two toothbrushes on the side of a sink."], "negative_caption": ["a tube of toothpaste and two toothbrushes on the side of a refrigerator."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1163387", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000398489.jpg", "positive_caption": ["a sleeping cat lays on a blanket."], "negative_caption": ["a sleeping dog lays on a blanket."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1144805", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000038816.jpg", "positive_caption": ["a refrigerator freezer sitting in a kitchen next to a bathroom."], "negative_caption": ["a microwave freezer sitting in a kitchen next to a bathroom."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1202427", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000285664.jpg", "positive_caption": ["vintage oven with door open and writing \"tips & techniques oven settings\""], "negative_caption": ["vintage microwave with door open and writing \"tips & techniques oven settings\""], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1210627", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000139163.jpg", "positive_caption": ["two bearded guys walking in a field one holding a frisbee."], "negative_caption": ["two bearded guys walking in a field one holding a snowboard."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1168922", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000419790.jpg", "positive_caption": ["a large long train and a person on a bike."], "negative_caption": ["a large long truck and a person on a bike."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1210838", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000111165.jpg", "positive_caption": ["an adult elephant and a child elephant walking in different directions."], "negative_caption": ["an adult horse and a child elephant walking in different directions."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1205727", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000323951.jpg", "positive_caption": ["someone walking with a surfboard on some sand"], "negative_caption": ["someone walking with a kite on some sand"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1203026", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000360175.jpg", "positive_caption": ["a star wars scene with toy figures with skateboard and umbrella."], "negative_caption": ["a star wars scene with toy figures with bat and umbrella."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1138168", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000394909.jpg", "positive_caption": ["two kids are flying a kite on a beach with a man."], "negative_caption": ["two kids are flying a frisbee on a beach with a man."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1097143", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000427655.jpg", "positive_caption": ["a horse is pulling a carriage with people down a street"], "negative_caption": ["a cow is pulling a carriage with people down a street"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1161392", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000167859.jpg", "positive_caption": ["an unmade bed that has pillows and blankets on it."], "negative_caption": ["an unmade couch that has pillows and blankets on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1284280", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000088265.jpg", "positive_caption": ["a big brown horse pulling a cart near a tree."], "negative_caption": ["a big brown cow pulling a cart near a tree."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1131387", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000446902.jpg", "positive_caption": ["a boy on the beach holding kite in both hands."], "negative_caption": ["a boy on the beach holding surfboard in both hands."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1254114", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000190056.jpg", "positive_caption": ["a couple of giraffe standing next to a fence."], "negative_caption": ["a couple of zebra standing next to a fence."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1001210", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000268838.jpg", "positive_caption": ["several sheep are in a grassy field with trees."], "negative_caption": ["several giraffe are in a grassy field with trees."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1069153", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000031345.jpg", "positive_caption": ["a cat is sleeping with a remote control on a couch."], "negative_caption": ["a cat is sleeping with a remote control on a bed."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1276445", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000523250.jpg", "positive_caption": ["a parrot with a yellow mohawk and an orange spot on his face perched way up high."], "negative_caption": ["a parrot with a yellow mohawk and an apple spot on his face perched way up high."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1257119", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000527580.jpg", "positive_caption": ["a train with passengers is standing on the track while some people are resting in the shade."], "negative_caption": ["a airplane with passengers is standing on the track while some people are resting in the shade."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1054550", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000456638.jpg", "positive_caption": ["a young woman holding a suitcase disembarking from a train car"], "negative_caption": ["a young woman holding a suitcase disembarking from a bus car"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1016790", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000010395.jpg", "positive_caption": ["a white teddy bear sitting on a bed."], "negative_caption": ["a white teddy bear sitting on a couch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1273836", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000195715.jpg", "positive_caption": ["a baseball and glove, sitting on a striped blanket."], "negative_caption": ["a baseball and surfboard, sitting on a striped blanket."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1259144", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000519853.jpg", "positive_caption": ["three people wading in shallow waters with a frisbee flying by"], "negative_caption": ["three people wading in shallow waters with a snowboard flying by"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1010944", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000369190.jpg", "positive_caption": ["a parking stand with cycles and a dog nearby."], "negative_caption": ["a parking stand with cycles and a horse nearby."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1142486", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000481327.jpg", "positive_caption": ["there are a bunch of dead flowers in this vase."], "negative_caption": ["there are a bunch of dead flowers in this clock."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1277795", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000010995.jpg", "positive_caption": ["a hotel room scene with focus on the bed and the window."], "negative_caption": ["a hotel room scene with focus on the couch and the window."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1125416", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000473002.jpg", "positive_caption": ["a pre-teen riding a skateboard on a street."], "negative_caption": ["a pre-teen riding a bat on a street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1290914", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000348087.jpg", "positive_caption": ["a very big pretty clock on a pole near the street."], "negative_caption": ["a very big pretty scissors on a pole near the street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1068056", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000255950.jpg", "positive_caption": ["cement ledge with orange in bowl and red plastic bag below."], "negative_caption": ["cement ledge with cake in bowl and red plastic bag below."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1106662", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000512495.jpg", "positive_caption": ["a plain white bathroom with a sink, tub and toilet."], "negative_caption": ["a plain white bathroom with a toaster, tub and toilet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1248054", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000443780.jpg", "positive_caption": ["a white toilet sitting inside of a restroom next to a sink."], "negative_caption": ["a white bed sitting inside of a restroom next to a sink."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1278613", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000558253.jpg", "positive_caption": ["a man on a horse beside some cattle on a road."], "negative_caption": ["a man on a cow beside some cattle on a road."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1191208", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000403150.jpg", "positive_caption": ["catcher catching a ball during a baseball game."], "negative_caption": ["catcher catching a glove during a baseball game."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1285297", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000397514.jpg", "positive_caption": ["a red and yellow bus next to some bikes"], "negative_caption": ["a red and yellow airplane next to some bikes"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1037743", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000171443.jpg", "positive_caption": ["there is a man standing i=on the beach playing frisbee"], "negative_caption": ["there is a man standing i=on the beach playing ball"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1123422", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000390975.jpg", "positive_caption": ["a children's playground slide made to look like an elephant"], "negative_caption": ["a children's playground slide made to look like an dog"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1010048", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000369093.jpg", "positive_caption": ["a freshly made pizza that is being served to someone."], "negative_caption": ["a freshly made sandwich that is being served to someone."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1284695", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000238528.jpg", "positive_caption": ["a woman sitting down with a child sharing a piece of cake."], "negative_caption": ["a woman sitting down with a child sharing a piece of pizza."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1125488", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000175443.jpg", "positive_caption": ["stuffed teddy bear placed in a lighted christmas tree"], "negative_caption": ["stuffed teddy giraffe placed in a lighted christmas tree"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1165150", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000177258.jpg", "positive_caption": ["a breakfast tray with pancakes and fruit with a cat standing near it."], "negative_caption": ["a breakfast tray with pancakes and fruit with a dog standing near it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1152170", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000319865.jpg", "positive_caption": ["a cat sitting inside a small, packed suitcase."], "negative_caption": ["a dog sitting inside a small, packed suitcase."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1001943", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000305030.jpg", "positive_caption": ["a clock on the top of a sign that is mounted on a building"], "negative_caption": ["a book on the top of a sign that is mounted on a building"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1120261", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000050637.jpg", "positive_caption": ["here is an image of an outside city with a clock."], "negative_caption": ["here is an image of an outside city with a scissors."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1060526", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000227316.jpg", "positive_caption": ["a clock on a tower on top of a brick building."], "negative_caption": ["a book on a tower on top of a brick building."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1217647", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000222512.jpg", "positive_caption": ["a mom holding her baby while working on her laptop."], "negative_caption": ["a mom holding her baby while working on her mouse."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1171924", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000001852.jpg", "positive_caption": ["a roll of cotton and a pair of scissors"], "negative_caption": ["a roll of cotton and a pair of vase"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1044494", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000348469.jpg", "positive_caption": ["a man in yellow jersey and red helmet holding a basebat bat."], "negative_caption": ["a man in yellow jersey and red helmet holding a baseball ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1199416", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000534876.jpg", "positive_caption": ["little boy on a baseball field about to hit the ball that has been pitched to him."], "negative_caption": ["little boy on a baseball field about to hit the glove that has been pitched to him."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1269401", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000009769.jpg", "positive_caption": ["a truck with a snow plow attached to the front."], "negative_caption": ["a car with a snow plow attached to the front."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1032071", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000069140.jpg", "positive_caption": ["a smiling man with a moustache is handed a plate by another man standing at a table with holiday decorations.."], "negative_caption": ["a smiling man with a moustache is handed a plate by another man standing at a bed with holiday decorations.."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1172651", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000362275.jpg", "positive_caption": ["a pregnant zebra walking through the tall grass."], "negative_caption": ["a pregnant giraffe walking through the tall grass."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1138612", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000294403.jpg", "positive_caption": ["a woman holding an umbrella on a dock."], "negative_caption": ["a woman holding an tie on a dock."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1082945", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000320020.jpg", "positive_caption": ["small spotted dog stands on the beach while the wind blows it's fur back"], "negative_caption": ["small spotted horse stands on the beach while the wind blows it's fur back"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1221453", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000218205.jpg", "positive_caption": ["a woman sitting at a table with a coffee cup and a halloween decoration."], "negative_caption": ["a woman sitting at a table with a coffee glass and a halloween decoration."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1059911", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000275515.jpg", "positive_caption": ["a white pickup truck drives through a grassy field."], "negative_caption": ["a white pickup car drives through a grassy field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1182676", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000042008.jpg", "positive_caption": ["a truck is parked on the side of a road near a bus."], "negative_caption": ["a car is parked on the side of a road near a bus."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1128993", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000259465.jpg", "positive_caption": ["a litte girl in a blue jacket holding a carrot."], "negative_caption": ["a litte girl in a blue jacket holding a cake."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1124634", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000442031.jpg", "positive_caption": ["a bedroom that has a king sized bed in it."], "negative_caption": ["a bedroom that has a king sized couch in it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1012699", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000244792.jpg", "positive_caption": ["a man is at a table of breakfast food."], "negative_caption": ["a man is at a bed of breakfast food."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1240376", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000575012.jpg", "positive_caption": ["a young woman talks on the phone as she sits on a fire hydrant."], "negative_caption": ["a young woman talks on the laptop as she sits on a fire hydrant."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1150837", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000284548.jpg", "positive_caption": ["a photograph of the wheels of a train."], "negative_caption": ["a photograph of the wheels of a truck."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1099734", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000137221.jpg", "positive_caption": ["a man in black jersey with a basebat bat."], "negative_caption": ["a man in black jersey with a baseball ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1239655", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000364166.jpg", "positive_caption": ["an adult and baby zebra looking onward on a field."], "negative_caption": ["an adult and baby elephant looking onward on a field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1146163", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000136915.jpg", "positive_caption": ["a man who is looking at a basebat bat."], "negative_caption": ["a man who is looking at a baseball ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1081768", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000217323.jpg", "positive_caption": ["a man on a snowboard walls in the snow"], "negative_caption": ["a man on a kite walls in the snow"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1283590", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000142340.jpg", "positive_caption": ["a white toilet with a blue seat on a display platform."], "negative_caption": ["a white bed with a blue seat on a display platform."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1091309", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000337662.jpg", "positive_caption": ["three young ladies are sitting at a table, while the other is in the fridge."], "negative_caption": ["three young ladies are sitting at a chair, while the other is in the fridge."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1141715", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000297180.jpg", "positive_caption": ["a woman sitting on a chair in front of a round table with a laptop computer, in a library."], "negative_caption": ["a woman sitting on a couch in front of a round table with a laptop computer, in a library."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1148825", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000506987.jpg", "positive_caption": ["a person looking at the back of a cell phone while holding a camera."], "negative_caption": ["a person looking at the back of a cell laptop while holding a camera."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1255038", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000062167.jpg", "positive_caption": ["a person is on a field with a dog and sheep."], "negative_caption": ["a person is on a field with a horse and sheep."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1128846", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000528525.jpg", "positive_caption": ["a close up of a young person holding a kite"], "negative_caption": ["a close up of a young person holding a bat"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1231649", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000523436.jpg", "positive_caption": ["a breakfast with a cup of coffee on the table."], "negative_caption": ["a breakfast with a bowl of coffee on the table."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1124846", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000201637.jpg", "positive_caption": ["a woman standing alone holding a large, white umbrella."], "negative_caption": ["a woman standing alone holding a large, white tie."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1206041", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000264976.jpg", "positive_caption": ["there is a cat standing in a toilet."], "negative_caption": ["there is a dog standing in a toilet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1091414", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000158035.jpg", "positive_caption": ["young lady holding a tennis racket with two hands."], "negative_caption": ["young lady holding a tennis ball with two hands."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1238895", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000244124.jpg", "positive_caption": ["an elephant in a ditch like area with trees in the background."], "negative_caption": ["an zebra in a ditch like area with trees in the background."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1018223", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000144065.jpg", "positive_caption": ["a mother and his boy sitting by his birthday cake."], "negative_caption": ["a mother and his boy sitting by his birthday pizza."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1132395", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000074656.jpg", "positive_caption": ["a man covered in tattoos talking on a phone."], "negative_caption": ["a man covered in tattoos talking on a laptop."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1120010", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000391688.jpg", "positive_caption": ["a young man riding a rail down some stairs on a skateboard."], "negative_caption": ["a young man riding a rail down some stairs on a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1177688", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000292365.jpg", "positive_caption": ["a striped cat standing next to an open toilet."], "negative_caption": ["a striped dog standing next to an open toilet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1068220", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000539883.jpg", "positive_caption": ["a flat screen tv sitting on top of a wooden bench."], "negative_caption": ["a flat screen tv sitting on top of a wooden hydrant."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1284782", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000283890.jpg", "positive_caption": ["a large vase stand in the middle of an elegant lobby."], "negative_caption": ["a large clock stand in the middle of an elegant lobby."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1059621", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000173053.jpg", "positive_caption": ["a large boat cruising through still blue water."], "negative_caption": ["a large airplane cruising through still blue water."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1191762", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000473204.jpg", "positive_caption": ["a small child in the saddle on a horse at the rodeo"], "negative_caption": ["a small child in the saddle on a cow at the rodeo"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1123891", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000188192.jpg", "positive_caption": ["a table with a cellphone, watch and pen."], "negative_caption": ["a chair with a cellphone, watch and pen."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1285679", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000068628.jpg", "positive_caption": ["a shirtless man is in mid air above some stairs on his skateboard."], "negative_caption": ["a shirtless man is in mid air above some stairs on his frisbee."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1259729", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000549361.jpg", "positive_caption": ["a boy standing against a wall while on a cell phone."], "negative_caption": ["a boy standing against a wall while on a cell laptop."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1037015", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000005535.jpg", "positive_caption": ["a colorful bus passes under a light on a city street."], "negative_caption": ["a colorful motorcycle passes under a light on a city street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1166146", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000235156.jpg", "positive_caption": ["a man with a tennis racket is standing on a court."], "negative_caption": ["a man with a tennis ball is standing on a court."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1051251", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000121677.jpg", "positive_caption": ["a piece of cake that has candles inside of it."], "negative_caption": ["a piece of pizza that has candles inside of it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1268407", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000043288.jpg", "positive_caption": ["a hotdog in a bun with a pickle next to a mobile phone."], "negative_caption": ["a hotdog in a bun with a pickle next to a mobile keyboard."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1215227", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000356528.jpg", "positive_caption": ["a laptop linked with a small screen using cables."], "negative_caption": ["a tv linked with a small screen using cables."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1091745", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000223905.jpg", "positive_caption": ["a person on a bike near a train"], "negative_caption": ["a person on a bike near a bus"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1017285", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000184386.jpg", "positive_caption": ["a message poster with a bed and writing above it"], "negative_caption": ["a message poster with a table and writing above it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1057832", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000509319.jpg", "positive_caption": ["colorful scissors sitting on a table lined with newsprint."], "negative_caption": ["colorful scissors sitting on a bed lined with newsprint."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1134813", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000343680.jpg", "positive_caption": ["a large brown pug down reaching up on a table."], "negative_caption": ["a large brown pug down reaching up on a chair."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1010811", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000541108.jpg", "positive_caption": ["female tennis player about to hit the ball"], "negative_caption": ["female tennis player about to hit the racket"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1238835", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000574404.jpg", "positive_caption": ["a baseball player in an orange jersey is swinging at the ball."], "negative_caption": ["a baseball player in an orange jersey is swinging at the glove."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1051234", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000369533.jpg", "positive_caption": ["a kite is flying over a waterway and under a dark sky."], "negative_caption": ["a surfboard is flying over a waterway and under a dark sky."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1021381", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000205222.jpg", "positive_caption": ["a cake that is less then half on a plate"], "negative_caption": ["a pizza that is less then half on a plate"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1199588", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000277689.jpg", "positive_caption": ["lavishly decorated cake and empty drinking glasses await their tropical guests"], "negative_caption": ["lavishly decorated pizza and empty drinking glasses await their tropical guests"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1260353", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000347370.jpg", "positive_caption": ["an orange that has a green colored peel."], "negative_caption": ["an apple that has a green colored peel."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1252231", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000504810.jpg", "positive_caption": ["a big sandwich sits on a plate with some french fries."], "negative_caption": ["a big carrot sits on a plate with some french fries."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1042119", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000414196.jpg", "positive_caption": ["a person playing with his phone, with a butterfly on it."], "negative_caption": ["a person playing with his laptop, with a butterfly on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1179854", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000161752.jpg", "positive_caption": ["a kite flying inside a gym with lights on."], "negative_caption": ["a snowboard flying inside a gym with lights on."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1134037", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000581157.jpg", "positive_caption": ["a cat laying on the floor next to a fish bowl"], "negative_caption": ["a cat laying on the floor next to a fish bottle"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1203624", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000427306.jpg", "positive_caption": ["an office cubicle with a desk, a laptop and desktop computers."], "negative_caption": ["an office cubicle with a desk, a mouse and desktop computers."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1045528", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000400853.jpg", "positive_caption": ["two people are riding a small motorcycle off-road."], "negative_caption": ["two people are riding a small airplane off-road."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1248541", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000093771.jpg", "positive_caption": ["a kid with a baseball bat with a ball being thrown to him."], "negative_caption": ["a kid with a baseball bat with a glove being thrown to him."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1171543", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000280819.jpg", "positive_caption": ["a guest looks over the plates of fruit on the table."], "negative_caption": ["a guest looks over the plates of fruit on the bed."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1004654", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000348488.jpg", "positive_caption": ["four black horses being driven across the sky on this ancient vase."], "negative_caption": ["four black horses being driven across the sky on this ancient toothbrush."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1123818", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000180764.jpg", "positive_caption": ["the man eats a donut with pink frosting and sprinkles in his kitchen."], "negative_caption": ["the man eats a banana with pink frosting and sprinkles in his kitchen."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1073439", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000221966.jpg", "positive_caption": ["an annoyed looking cat laying down in a bowl"], "negative_caption": ["an annoyed looking dog laying down in a bowl"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1266274", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000225670.jpg", "positive_caption": ["a brown dog leaping to catch a flying disc."], "negative_caption": ["a brown bear leaping to catch a flying disc."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1086458", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000551350.jpg", "positive_caption": ["a wooden table sititng under a big tree"], "negative_caption": ["a wooden chair sititng under a big tree"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1129087", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000243190.jpg", "positive_caption": ["a coleslaw mixture in a bowl with a spoon."], "negative_caption": ["a coleslaw mixture in a bowl with a knife."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1244845", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000241867.jpg", "positive_caption": ["a orange and cream colored bus parked outside a small market."], "negative_caption": ["a cake and cream colored bus parked outside a small market."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1248354", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000487898.jpg", "positive_caption": ["young girl playing with a soccer ball inside the house."], "negative_caption": ["young girl playing with a soccer racket inside the house."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1275896", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000454818.jpg", "positive_caption": ["a large brown dog laying inside of a car."], "negative_caption": ["a large brown bear laying inside of a car."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1288509", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000016879.jpg", "positive_caption": ["there is a male frisbee player about to catch the frisbee"], "negative_caption": ["there is a male frisbee player about to catch the ball"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1168620", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000578343.jpg", "positive_caption": ["a room with a desk and dresser holding a tv"], "negative_caption": ["a room with a desk and dresser holding a phone"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1287130", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000481035.jpg", "positive_caption": ["a neatly made bed with several pillows in a hotel room."], "negative_caption": ["a neatly made couch with several pillows in a hotel room."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1035184", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000190211.jpg", "positive_caption": ["small dog jumping to catch a frisbee near a playground."], "negative_caption": ["small dog jumping to catch a ball near a playground."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1213761", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000049194.jpg", "positive_caption": ["a young tennis player tries to hit the ball."], "negative_caption": ["a young tennis player tries to hit the racket."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1140463", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000492363.jpg", "positive_caption": ["a cake shop store front with a cake board side in front."], "negative_caption": ["a sandwich shop store front with a sandwich board side in front."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1193538", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000438560.jpg", "positive_caption": ["an old brown car is parked on the grass."], "negative_caption": ["an old brown train is parked on the grass."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1068083", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000188667.jpg", "positive_caption": ["a cat looking up towards the ceiling in front of a window with broken blinds."], "negative_caption": ["a dog looking up towards the ceiling in front of a window with broken blinds."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1242914", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000365325.jpg", "positive_caption": ["a baby boy falls asleep sitting up with a wii remote in his hand"], "negative_caption": ["a baby boy falls asleep sitting up with a wii tv in his hand"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1028236", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000149005.jpg", "positive_caption": ["a dog with a toy in its mouth while running across a beach."], "negative_caption": ["a horse with a toy in its mouth while running across a beach."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1228866", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000542284.jpg", "positive_caption": ["a girl sitting in a chair talking on a cellphone."], "negative_caption": ["a girl sitting in a couch talking on a cellphone."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1044087", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000411070.jpg", "positive_caption": ["a living room has a couch, a lamp, and a fireplace."], "negative_caption": ["a living room has a bed, a lamp, and a fireplace."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1119078", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000013415.jpg", "positive_caption": ["a railroad conductor looking off the side of the train"], "negative_caption": ["a railroad conductor looking off the side of the bus"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1197517", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000254638.jpg", "positive_caption": ["a man riding a skateboard downs the side of a wooden ramp."], "negative_caption": ["a man riding a frisbee downs the side of a wooden ramp."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1087917", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000140826.jpg", "positive_caption": ["white jet airplane with its light on on a runway."], "negative_caption": ["white jet truck with its light on on a runway."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1091882", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000533281.jpg", "positive_caption": ["an image of firestone grill cooking pizza in the oven"], "negative_caption": ["an image of firestone grill cooking sandwich in the oven"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1209322", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000164179.jpg", "positive_caption": ["a pizza on a cutting board topped with bacon and vegetables."], "negative_caption": ["a sandwich on a cutting board topped with bacon and vegetables."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1207355", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000500116.jpg", "positive_caption": ["there is a frisbee team taking a team photo"], "negative_caption": ["there is a ball team taking a team photo"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1123643", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000539938.jpg", "positive_caption": ["a long train is coming down some tracks"], "negative_caption": ["a long bus is coming down some tracks"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1167051", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000153445.jpg", "positive_caption": ["a nicely-decorated living room with a television and couch is pictured."], "negative_caption": ["a nicely-decorated living room with a television and bed is pictured."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1114249", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000459919.jpg", "positive_caption": ["a train station with a train driving into it."], "negative_caption": ["a train station with a bus driving into it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1235200", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000565797.jpg", "positive_caption": ["an orange cat hiding on the wheel of a red car."], "negative_caption": ["an orange dog hiding on the wheel of a red car."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1000427", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000370689.jpg", "positive_caption": ["a small dinner table with chairs, a pouring picture and a mirror above it."], "negative_caption": ["a small dinner bed with chairs, a pouring picture and a mirror above it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1261272", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000466239.jpg", "positive_caption": ["an amtrak train traveling under a train bridge."], "negative_caption": ["an amtrak truck traveling under a train bridge."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1212212", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000202470.jpg", "positive_caption": ["a woman holding an umbrella can barely be seen as she crosses the street at night."], "negative_caption": ["a woman holding an tie can barely be seen as she crosses the street at night."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1256682", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000505862.jpg", "positive_caption": ["a woman in a busy outdoor cafe holds up a pizza on a plate."], "negative_caption": ["a woman in a busy outdoor cafe holds up a sandwich on a plate."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1095876", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000370279.jpg", "positive_caption": ["a young child stands on a board while using a video game remote."], "negative_caption": ["a young child stands on a board while using a video game tv."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1163432", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000389445.jpg", "positive_caption": ["a bathroom with a sink, counter and electrical outlet."], "negative_caption": ["a bathroom with a toaster, counter and electrical outlet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1044969", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000015735.jpg", "positive_caption": ["a person is holding a hot dog in their hand."], "negative_caption": ["a person is holding a hot bird in their hand."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1162041", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000124004.jpg", "positive_caption": ["three seats are pushed in at the table with another table off in the distance."], "negative_caption": ["three seats are pushed in at the table with another bed off in the distance."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1180745", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000397045.jpg", "positive_caption": ["a cat sitting on the back of a bench while looking upward."], "negative_caption": ["a dog sitting on the back of a bench while looking upward."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1045972", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000508418.jpg", "positive_caption": ["a group of people standing on top of a field flying a kite."], "negative_caption": ["a group of people standing on top of a field flying a bat."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1119203", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000405355.jpg", "positive_caption": ["a train sits on a train track against a shrub"], "negative_caption": ["a truck sits on a train track against a shrub"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1159500", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000472211.jpg", "positive_caption": ["a woman is helping a red kite fly in a park."], "negative_caption": ["a woman is helping a red frisbee fly in a park."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1269311", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000195353.jpg", "positive_caption": ["a cat is sitting in front of a window."], "negative_caption": ["a dog is sitting in front of a window."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1273554", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000473299.jpg", "positive_caption": ["a person on a snowboard riding it in the snow."], "negative_caption": ["a person on a kite riding it in the snow."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1048869", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000278203.jpg", "positive_caption": ["a man carrying a bag and some skis down a street."], "negative_caption": ["a man carrying a bag and some skateboard down a street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1244302", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000008190.jpg", "positive_caption": ["a man standing on his surfboard riding a big wave"], "negative_caption": ["a man standing on his snowboard riding a big wave"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1162830", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000108853.jpg", "positive_caption": ["some flowers are siting on a dimly lit table"], "negative_caption": ["some flowers are siting on a dimly lit chair"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1037247", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000057265.jpg", "positive_caption": ["a woman with an umbrella and a man walking."], "negative_caption": ["a woman with an tie and a man walking."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1055750", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000370591.jpg", "positive_caption": ["a group of solders cutting up a sheet cake."], "negative_caption": ["a group of solders cutting up a sheet pizza."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1103758", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000184266.jpg", "positive_caption": ["a man holding a tennis racket while on the tennis court"], "negative_caption": ["a man holding a tennis ball while on the tennis court"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1133272", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000379837.jpg", "positive_caption": ["a woman holds a cake in front of a baby in a high chair."], "negative_caption": ["a woman holds a pizza in front of a baby in a high chair."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1125102", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000563083.jpg", "positive_caption": ["the light from a phone shines on a thumb."], "negative_caption": ["the light from a keyboard shines on a thumb."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1232489", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000364699.jpg", "positive_caption": ["a colorful three level vase sitting on a white counter."], "negative_caption": ["a colorful three level toothbrush sitting on a white counter."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1240477", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000051685.jpg", "positive_caption": ["an single prop red and white airplane with four wings"], "negative_caption": ["an single prop red and white car with four wings"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1106837", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000014108.jpg", "positive_caption": ["a small black dog watching an animal on a tv screen."], "negative_caption": ["a small black bird watching an animal on a tv screen."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1263785", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000107339.jpg", "positive_caption": ["a young girl is using a video game remote control."], "negative_caption": ["a young girl is using a video game tv control."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1089185", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000068833.jpg", "positive_caption": ["a kitchen with lots of cupboard space and a microwave oven."], "negative_caption": ["a kitchen with lots of cupboard space and a sink oven."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1255630", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000422240.jpg", "positive_caption": ["a man is holding a baseball bat in front of a banner"], "negative_caption": ["a man is holding a baseball racket in front of a banner"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1216734", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000490415.jpg", "positive_caption": ["a man in a park area flying a kite"], "negative_caption": ["a man in a park area flying a frisbee"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1013655", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000374982.jpg", "positive_caption": ["a young girl looking at a huge pizza in amazement."], "negative_caption": ["a young girl looking at a huge sandwich in amazement."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1285491", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000379210.jpg", "positive_caption": ["a grey cat is sitting on a bench"], "negative_caption": ["a grey dog is sitting on a bench"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1271821", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000194786.jpg", "positive_caption": ["a young person is jumping to catch the frisbee between his legs."], "negative_caption": ["a young person is jumping to catch the snowboard between his legs."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1101757", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000408047.jpg", "positive_caption": ["a bus at a bus stop along a street filled with taxis."], "negative_caption": ["a bicycle at a bus stop along a street filled with taxis."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1189578", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000165752.jpg", "positive_caption": ["a dog that is sitting down with a frisbee."], "negative_caption": ["a bird that is sitting down with a frisbee."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1175925", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000386257.jpg", "positive_caption": ["a clock is sitting below an american flag."], "negative_caption": ["a scissors is sitting below an american flag."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1209901", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000052020.jpg", "positive_caption": ["a brown horse eating hay from the ground."], "negative_caption": ["a brown cow eating hay from the ground."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1237101", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000301977.jpg", "positive_caption": ["a cow standing next to a shelf with many drinks."], "negative_caption": ["a dog standing next to a shelf with many drinks."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1129634", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000473124.jpg", "positive_caption": ["an orange and an orange juicer beside pulp in a strainer"], "negative_caption": ["an apple and an orange juicer beside pulp in a strainer"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1079550", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000168626.jpg", "positive_caption": ["an empty bathroom with a toilet and hand rails"], "negative_caption": ["an empty bathroom with a table and hand rails"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1015275", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000236162.jpg", "positive_caption": ["two cats laying on a couch with books"], "negative_caption": ["two cats laying on a bed with books"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1025050", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000549220.jpg", "positive_caption": ["a dog on a leash trying to ride a skateboard."], "negative_caption": ["a dog on a leash trying to ride a frisbee."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1296001", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000016961.jpg", "positive_caption": ["a man with a stick pushing himself by skateboard"], "negative_caption": ["a man with a stick pushing himself by bat"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1214635", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000485452.jpg", "positive_caption": ["a toilet sits between a sink and bathtub"], "negative_caption": ["a bed sits between a sink and bathtub"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1076010", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000083142.jpg", "positive_caption": ["a zebra is standing in the middle of a road way."], "negative_caption": ["a horse is standing in the middle of a road way."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1094587", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000450247.jpg", "positive_caption": ["a cat stretching out in a blue briefcase."], "negative_caption": ["a dog stretching out in a blue briefcase."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1002887", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000355304.jpg", "positive_caption": ["young boy eating a big donut in a restaurant."], "negative_caption": ["young boy eating a big sandwich in a restaurant."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1177916", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000152987.jpg", "positive_caption": ["an elephant walking through underbrush next to a fence."], "negative_caption": ["an horse walking through underbrush next to a fence."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1266097", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000360844.jpg", "positive_caption": ["adult and a baby zebra walking around on a dirt ground."], "negative_caption": ["adult and a baby elephant walking around on a dirt ground."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1229362", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000024195.jpg", "positive_caption": ["there is a green bus that is stopped at the bus stop"], "negative_caption": ["there is a green airplane that is stopped at the bus stop"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1061407", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000539683.jpg", "positive_caption": ["a cat laying inside of a white bathroom sink."], "negative_caption": ["a dog laying inside of a white bathroom sink."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1228012", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000555983.jpg", "positive_caption": ["a man is riding a motorcycle on one wheel."], "negative_caption": ["a man is riding a bicycle on one wheel."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1014952", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000317592.jpg", "positive_caption": ["zoo visitors look on at an adult and baby giraffe."], "negative_caption": ["zoo visitors look on at an adult and baby zebra."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1136129", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000477949.jpg", "positive_caption": ["a bunch of flower on a wooden table."], "negative_caption": ["a bunch of flower on a wooden chair."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1006790", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000014248.jpg", "positive_caption": ["a child smiles at the camera while laying on a bed."], "negative_caption": ["a child smiles at the camera while laying on a couch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1058245", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000200745.jpg", "positive_caption": ["a soccer goalie diving to keep the ball out of the net."], "negative_caption": ["a soccer goalie diving to keep the racket out of the net."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1132434", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000109827.jpg", "positive_caption": ["a teddy bear leaning against a tree next to the road."], "negative_caption": ["a teddy cat leaning against a tree next to the road."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1246540", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000135872.jpg", "positive_caption": ["a desk containing a desktop and laptop computers."], "negative_caption": ["a desk containing a desktop and mouse computers."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1144720", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000397773.jpg", "positive_caption": ["a close up of a plate of pasta containing broccoli."], "negative_caption": ["a close up of a plate of pasta containing carrot."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1003926", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000134558.jpg", "positive_caption": ["a young boy wearing a blue shirt holding a tennis racket"], "negative_caption": ["a young boy wearing a blue shirt holding a tennis ball"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1187242", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000388619.jpg", "positive_caption": ["a boat sitting in the water with people on it while their bikes stand in the sand."], "negative_caption": ["a truck sitting in the water with people on it while their bikes stand in the sand."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1247934", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000181714.jpg", "positive_caption": ["an animation of a girl holding an umbrella is shown."], "negative_caption": ["an animation of a girl holding an tie is shown."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1002845", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000031049.jpg", "positive_caption": ["a dog sits on his back on top of a beige sofa."], "negative_caption": ["a bear sits on his back on top of a beige sofa."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1228995", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000012010.jpg", "positive_caption": ["a close up of a pizza with broccoli and bacon on it"], "negative_caption": ["a close up of a sandwich with broccoli and bacon on it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1208548", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000498759.jpg", "positive_caption": ["a camera films a skateboard at high speed"], "negative_caption": ["a camera films a kite at high speed"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1071719", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000018575.jpg", "positive_caption": ["two plates, one with a sandwich and fries, the other with just a sandwich and a pickle."], "negative_caption": ["two plates, one with a pizza and fries, the other with just a sandwich and a pickle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1056852", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000213280.jpg", "positive_caption": ["black and white photograph of people standing in shore next to bus in water."], "negative_caption": ["black and white photograph of people standing in shore next to airplane in water."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1264363", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000072275.jpg", "positive_caption": ["the wooden plate has a banana, peaches, and a green apple."], "negative_caption": ["the wooden plate has a carrot, peaches, and a green apple."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1033689", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000486290.jpg", "positive_caption": ["table display of different sized and colored vases"], "negative_caption": ["bed display of different sized and colored vases"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1247573", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000004495.jpg", "positive_caption": ["a corner of a living room with a tv in it."], "negative_caption": ["a corner of a living room with a phone in it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1013484", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000488869.jpg", "positive_caption": ["a female tennis-player with her racket in-hand in front of a crowd of onlookers."], "negative_caption": ["a female tennis-player with her kite in-hand in front of a crowd of onlookers."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1059083", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000229391.jpg", "positive_caption": ["a man is walking towards a truck with bikes"], "negative_caption": ["a man is walking towards a car with bikes"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1167406", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000030143.jpg", "positive_caption": ["an open laptop computer sitting on top of a desk."], "negative_caption": ["an open tv computer sitting on top of a desk."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1089697", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000521357.jpg", "positive_caption": ["a bunch of bottles that are inside of a refrigerator."], "negative_caption": ["a bunch of bottles that are inside of a microwave."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1209227", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000205035.jpg", "positive_caption": ["a man with his dog out near a lake."], "negative_caption": ["a man with his horse out near a lake."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1176667", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000427111.jpg", "positive_caption": ["an aerial view of a boat pulling to skiers behind."], "negative_caption": ["an aerial view of a airplane pulling to skiers behind."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1161617", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000171809.jpg", "positive_caption": ["a cat sitting on a bench with a bike behind it."], "negative_caption": ["a dog sitting on a bench with a bike behind it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1067866", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000263211.jpg", "positive_caption": ["a giraffe walking through a lush green field."], "negative_caption": ["a zebra walking through a lush green field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1158886", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000114335.jpg", "positive_caption": ["a pizza with toppings being put in the oven."], "negative_caption": ["a sandwich with toppings being put in the oven."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1207033", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000492816.jpg", "positive_caption": ["a white cat is laying on a pan and posing for a picture."], "negative_caption": ["a white dog is laying on a pan and posing for a picture."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1182727", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000145149.jpg", "positive_caption": ["a man with a shirt and tie just looking at the camera"], "negative_caption": ["a man with a shirt and suitcase just looking at the camera"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1093854", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000269254.jpg", "positive_caption": ["a woman helping another woman hold a surfboard while she is on the back of a scooter."], "negative_caption": ["a woman helping another woman hold a kite while she is on the back of a scooter."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1283929", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000264017.jpg", "positive_caption": ["an image of a slice of pizza on a plate"], "negative_caption": ["an image of a slice of sandwich on a plate"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1013174", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000233236.jpg", "positive_caption": ["the room with the blue couch is very messy."], "negative_caption": ["the room with the blue bed is very messy."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1111340", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000074853.jpg", "positive_caption": ["a man riding a skateboard over a metal rail in a parking lot."], "negative_caption": ["a man riding a kite over a metal rail in a parking lot."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1177578", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000209322.jpg", "positive_caption": ["a toilet with a water closet in a small blue and white bathroom."], "negative_caption": ["a bed with a water closet in a small blue and white bathroom."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1007621", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000278352.jpg", "positive_caption": ["few people playing with frisbee in the park."], "negative_caption": ["few people playing with ball in the park."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1086965", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000468541.jpg", "positive_caption": ["a brown and white dog wearing a neck tie."], "negative_caption": ["a brown and white horse wearing a neck tie."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1009908", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000273321.jpg", "positive_caption": ["a person off to the side is wearing an orange tank top and a man in the middle is jumping up in the air catching something and across from the gym is a woman and a child."], "negative_caption": ["a person off to the side is wearing an pizza tank top and a man in the middle is jumping up in the air catching something and across from the gym is a woman and a child."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1040688", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000154363.jpg", "positive_caption": ["a white toilet and a bath in a room."], "negative_caption": ["a white bed and a bath in a room."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1106142", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000149770.jpg", "positive_caption": ["a man riding a wave on top of a surfboard."], "negative_caption": ["a man riding a wave on top of a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1125782", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000186821.jpg", "positive_caption": ["a couple of people walking down the side walk near a a convertible bus."], "negative_caption": ["a couple of people walking down the side walk near a a convertible motorcycle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1136204", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000049731.jpg", "positive_caption": ["a man flying through the air while riding a snowboard."], "negative_caption": ["a man flying through the air while riding a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1245194", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000121897.jpg", "positive_caption": ["baseball catcher catching a ball that appears to be high and outside."], "negative_caption": ["baseball catcher catching a glove that appears to be high and outside."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1079587", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000018350.jpg", "positive_caption": ["a large tower with a large clock on top."], "negative_caption": ["a large tower with a large scissors on top."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1247425", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000384553.jpg", "positive_caption": ["man riding an elephant into water surrounded by forest"], "negative_caption": ["man riding an horse into water surrounded by forest"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1000156", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000372652.jpg", "positive_caption": ["a small black bear cub investigates a garbage can at the edge of the forest."], "negative_caption": ["a small black cat cub investigates a garbage can at the edge of the forest."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1101222", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000377652.jpg", "positive_caption": ["a person in a wetsuit being pulled out of the water by a kite board."], "negative_caption": ["a person in a wetsuit being pulled out of the water by a snowboard board."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1208204", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000211042.jpg", "positive_caption": ["a cat pears into the bowl of a toilet."], "negative_caption": ["a horse pears into the bowl of a toilet."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1022967", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000519573.jpg", "positive_caption": ["a person on a skateboard on a city street."], "negative_caption": ["a person on a bat on a city street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1095411", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000277032.jpg", "positive_caption": ["a man standing next to backpacks and skis and poles."], "negative_caption": ["a man standing next to backpacks and snowboard and poles."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1124765", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000308120.jpg", "positive_caption": ["a decorated cake and a baseball cap on display on a table."], "negative_caption": ["a decorated sandwich and a baseball cap on display on a table."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1288203", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000138477.jpg", "positive_caption": ["a person flying a blue kite in an open field"], "negative_caption": ["a person flying a blue frisbee in an open field"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1005799", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000191126.jpg", "positive_caption": ["the white and blue bird is standing on a wooden post."], "negative_caption": ["the white and blue cat is standing on a wooden post."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1159010", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000244218.jpg", "positive_caption": ["a refrigerator sitting in front of a vandalized wall."], "negative_caption": ["a microwave sitting in front of a vandalized wall."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1022268", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000422221.jpg", "positive_caption": ["a large gray elephant standing under a blue covering."], "negative_caption": ["a large gray horse standing under a blue covering."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1063589", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000163600.jpg", "positive_caption": ["a man holding a toothbrush with a valentines message tied to it."], "negative_caption": ["a man holding a clock with a valentines message tied to it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1246134", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000569700.jpg", "positive_caption": ["a vase sitting next to a mirror filled with flowers"], "negative_caption": ["a clock sitting next to a mirror filled with flowers"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1247597", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000294783.jpg", "positive_caption": ["large open floor space with makeshift bed and shelving with books."], "negative_caption": ["large open floor space with makeshift table and shelving with books."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1163555", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000251065.jpg", "positive_caption": ["a toilet bowl with a black toilet seat cover"], "negative_caption": ["a bed bowl with a black toilet seat cover"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1023378", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000047121.jpg", "positive_caption": ["a cat drinking from a sink faucet that was left running."], "negative_caption": ["a dog drinking from a sink faucet that was left running."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1225798", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000019142.jpg", "positive_caption": ["a statue on top of a giant clock tower near a flag."], "negative_caption": ["a statue on top of a giant book tower near a flag."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1105544", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000491130.jpg", "positive_caption": ["a man riding a snowboard on top of a snow covered slope."], "negative_caption": ["a man riding a kite on top of a snow covered slope."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1169917", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000020254.jpg", "positive_caption": ["a man holding an umbrella and a flashlight"], "negative_caption": ["a man holding an backpack and a flashlight"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1071526", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000083013.jpg", "positive_caption": ["an elephant stands in an enclosure at a zoo"], "negative_caption": ["an horse stands in an enclosure at a zoo"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1130458", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000301991.jpg", "positive_caption": ["a bride is eating steak at a table."], "negative_caption": ["a bride is eating steak at a bed."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1075697", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000344005.jpg", "positive_caption": ["two people on the beach are playing frisbee."], "negative_caption": ["two people on the beach are playing ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1176728", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000079545.jpg", "positive_caption": ["a flock of sheep graze in wooded hills along a river."], "negative_caption": ["a flock of cow graze in wooded hills along a river."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1144587", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000290234.jpg", "positive_caption": ["a young man in a black car speaking on a cell phone."], "negative_caption": ["a young man in a black train speaking on a cell phone."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1239433", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000226368.jpg", "positive_caption": ["a blue piece of luggage sitting on top of a wooden chair."], "negative_caption": ["a blue piece of luggage sitting on top of a wooden table."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1183465", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000470624.jpg", "positive_caption": ["a boat traveling across a large body of water near a large mountain."], "negative_caption": ["a truck traveling across a large body of water near a large mountain."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1100471", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000283833.jpg", "positive_caption": ["a dog wearing goggles and a red collar sits in the backseat of a car with its tongue hanging out."], "negative_caption": ["a dog wearing goggles and a red collar sits in the backseat of a bicycle with its tongue hanging out."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1294207", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000192798.jpg", "positive_caption": ["a man taking a pizza with some drink on a glass"], "negative_caption": ["a man taking a pizza with some drink on a fork"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1134195", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000205542.jpg", "positive_caption": ["a stuffed teddy bear sitting on a metal sculpture"], "negative_caption": ["a stuffed teddy bird sitting on a metal sculpture"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1028758", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000412151.jpg", "positive_caption": ["a man and a boy are talking about a bicycle in a store."], "negative_caption": ["a man and a boy are talking about a motorcycle in a store."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1000225", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000332627.jpg", "positive_caption": ["a woman with a tennis racket on the court."], "negative_caption": ["a woman with a tennis ball on the court."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1291814", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000267932.jpg", "positive_caption": ["a desk with a banana a keyboard and a mouse"], "negative_caption": ["a desk with a sandwich a keyboard and a mouse"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1158219", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000208748.jpg", "positive_caption": ["many people at a long table with drinks and food"], "negative_caption": ["many people at a long bed with drinks and food"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1195520", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000139113.jpg", "positive_caption": ["a man in a purple shirt holding a soccer ball next to other soccer players."], "negative_caption": ["a man in a purple shirt holding a soccer racket next to other soccer players."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1238648", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000462148.jpg", "positive_caption": ["there is a mp3 player that is next to a cell phone"], "negative_caption": ["there is a mp3 player that is next to a cell keyboard"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1172061", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000433460.jpg", "positive_caption": ["on a sunny afternoon, the herd of zebra are romping in the field."], "negative_caption": ["on a sunny afternoon, the herd of elephant are romping in the field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1003471", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000307531.jpg", "positive_caption": ["a person is in the distance while a brown dog is in midair and is running after a frisbee."], "negative_caption": ["a person is in the distance while a brown horse is in midair and is running after a frisbee."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1236983", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000001647.jpg", "positive_caption": ["a piece of bread with wrapping around it with scissors."], "negative_caption": ["a piece of bread with wrapping around it with vase."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1044468", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000003716.jpg", "positive_caption": ["a woman laying on a couch looking at a laptop"], "negative_caption": ["a woman laying on a bed looking at a laptop"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1292782", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000229150.jpg", "positive_caption": ["a man walks down a street with an elephant."], "negative_caption": ["a man walks down a street with an horse."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1213382", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000094055.jpg", "positive_caption": ["a man on a horse in riding gear looking onward."], "negative_caption": ["a man on a cow in riding gear looking onward."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1190259", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000302292.jpg", "positive_caption": ["a man holding a small cat in his hands."], "negative_caption": ["a man holding a small dog in his hands."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1180606", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000421834.jpg", "positive_caption": ["a bird that is sitting on a bird feeder."], "negative_caption": ["a cat that is sitting on a bird feeder."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1197408", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000069224.jpg", "positive_caption": ["a couple of people eating some doughnuts on a table"], "negative_caption": ["a couple of people eating some doughnuts on a chair"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1103408", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000348931.jpg", "positive_caption": ["an elephant is walking in an open area with a log on the ground behind him."], "negative_caption": ["an bear is walking in an open area with a log on the ground behind him."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1289018", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000056567.jpg", "positive_caption": ["there is a plate of food and a pizza on a table."], "negative_caption": ["there is a plate of food and a sandwich on a table."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1170004", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000290093.jpg", "positive_caption": ["woman stands at the desk next to the bed"], "negative_caption": ["woman stands at the desk next to the couch"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1275970", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000363286.jpg", "positive_caption": ["a train filled with passengers with yellow seats."], "negative_caption": ["a truck filled with passengers with yellow seats."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1196629", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000340329.jpg", "positive_caption": ["a small passenger train sits on tracks near a fence and rose trainhes."], "negative_caption": ["a small passenger bus sits on tracks near a fence and rose bushes."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1190472", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000386436.jpg", "positive_caption": ["cow wearing sunglasses is looked upon by other cow in field."], "negative_caption": ["elephant wearing sunglasses is looked upon by other cow in field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1144899", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000314383.jpg", "positive_caption": ["a man riding a skateboard through a empty lobby."], "negative_caption": ["a man riding a frisbee through a empty lobby."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1139761", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000482071.jpg", "positive_caption": ["a bear is knee high in the grass."], "negative_caption": ["a bird is knee high in the grass."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1116493", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000570465.jpg", "positive_caption": ["several slices of bread with side salads on a table."], "negative_caption": ["several slices of bread with side salads on a chair."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1003866", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000404546.jpg", "positive_caption": ["a person on skis makes their way through the snow"], "negative_caption": ["a person on snowboard makes their way through the snow"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1095494", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000062518.jpg", "positive_caption": ["there is a somewhat short train moving along a track"], "negative_caption": ["there is a somewhat short bus moving along a track"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1070631", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000281711.jpg", "positive_caption": ["wide open kitchen area with wooden floors and small refrigerator."], "negative_caption": ["wide open kitchen area with wooden floors and small microwave."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1051581", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000405836.jpg", "positive_caption": ["series of small portions of food being put into a small oven."], "negative_caption": ["series of small portions of food being put into a small toaster."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1132416", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000468784.jpg", "positive_caption": ["a couple cutting their wedding cake at their reception."], "negative_caption": ["a couple cutting their wedding pizza at their reception."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1012381", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000142483.jpg", "positive_caption": ["a picture of two slices of pizza resting on a white plate."], "negative_caption": ["a picture of two slices of sandwich resting on a white plate."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1170931", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000211618.jpg", "positive_caption": ["a black and white cow standing in a field."], "negative_caption": ["a black and white dog standing in a field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1265970", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000102644.jpg", "positive_caption": ["a bathroom with a glass shower door, a toilet and a towel handle."], "negative_caption": ["a bathroom with a cup shower door, a toilet and a towel handle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1053152", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000324203.jpg", "positive_caption": ["a bowl filled with hot dogs next to a bowl of chili."], "negative_caption": ["a glass filled with hot dogs next to a bowl of chili."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1110299", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000399790.jpg", "positive_caption": ["a baseball pitcher throwing a ball during a baseball game."], "negative_caption": ["a baseball pitcher throwing a glove during a baseball game."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1214356", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000026942.jpg", "positive_caption": ["a cat sitting in a chair at a table with a book on it."], "negative_caption": ["a cat sitting in a chair at a table with a clock on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1002013", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000579303.jpg", "positive_caption": ["a couple of plates of food that is on a table."], "negative_caption": ["a couple of plates of food that is on a bed."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1275563", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000577364.jpg", "positive_caption": ["a baby elephant nudges it's huge parent with it's trunk."], "negative_caption": ["a baby horse nudges it's huge parent with it's trunk."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1145747", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000357379.jpg", "positive_caption": ["a person in the water with a surfboard."], "negative_caption": ["a person in the water with a kite."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1050240", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000534673.jpg", "positive_caption": ["a blue and white bus with large windows on it."], "negative_caption": ["a blue and white airplane with large windows on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1264549", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000530998.jpg", "positive_caption": ["a man in red shirt playing a game with frisbee."], "negative_caption": ["a man in red shirt playing a game with ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1071857", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000287959.jpg", "positive_caption": ["the sandwich had been cut and was ready to eat."], "negative_caption": ["the pizza had been cut and was ready to eat."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1162397", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000299593.jpg", "positive_caption": ["a double decked bus sitting on the curb."], "negative_caption": ["a double decked bicycle sitting on the curb."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1114820", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000415723.jpg", "positive_caption": ["a dog in the air with frisbee in mouth above grass by fence with spectators."], "negative_caption": ["a giraffe in the air with frisbee in mouth above grass by fence with spectators."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1086997", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000428291.jpg", "positive_caption": ["a table full of food with a glass of water."], "negative_caption": ["a bed full of food with a glass of water."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1193554", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000188804.jpg", "positive_caption": ["woman with big headphones on stands at table in front of monitor"], "negative_caption": ["woman with big headphones on stands at bed in front of monitor"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1089816", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000559067.jpg", "positive_caption": ["a dog sits in an open suitcase that is on a hardwood floor."], "negative_caption": ["a horse sits in an open suitcase that is on a hardwood floor."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1236251", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000437231.jpg", "positive_caption": ["two dogs are resting on a chair that has a blanket on it."], "negative_caption": ["two dogs are resting on a couch that has a blanket on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1153450", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000409985.jpg", "positive_caption": ["a man is smiling and giving thumbs up to a pizza topped with fries"], "negative_caption": ["a man is smiling and giving thumbs up to a sandwich topped with fries"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1268647", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000439306.jpg", "positive_caption": ["the back of a moving truck that has a man standing on a lift with a royalty style chair next to him."], "negative_caption": ["the back of a moving truck that has a man standing on a lift with a royalty style couch next to him."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1039554", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000256260.jpg", "positive_caption": ["a man in white shirt petting the cheek of an elephant."], "negative_caption": ["a man in white shirt petting the cheek of an bear."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1010357", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000323442.jpg", "positive_caption": ["two people smile sitting at a table covered with wine glasses."], "negative_caption": ["two people smile sitting at a bed covered with wine glasses."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1044653", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000468457.jpg", "positive_caption": ["this pizza has boiled eggs and onions on it."], "negative_caption": ["this sandwich has boiled eggs and onions on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1088975", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000389445.jpg", "positive_caption": ["personal care items and jewelry are next to a bathroom sink."], "negative_caption": ["personal care items and jewelry are next to a bathroom refrigerator."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1044971", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000498638.jpg", "positive_caption": ["a boy reaching up so he can hit a tennis ball"], "negative_caption": ["a boy reaching up so he can hit a tennis racket"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1224709", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000380388.jpg", "positive_caption": ["a yellow fronted train is going down the tracks."], "negative_caption": ["a yellow fronted bus is going down the tracks."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1070187", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000248111.jpg", "positive_caption": ["a white refrigerator freezer sitting inside of a kitchen."], "negative_caption": ["a white microwave freezer sitting inside of a kitchen."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1233378", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000233238.jpg", "positive_caption": ["a long table with many containers of food on it and many people around it"], "negative_caption": ["a long bed with many containers of food on it and many people around it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1202757", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000007304.jpg", "positive_caption": ["a small girl in action on a court with a racket."], "negative_caption": ["a small girl in action on a court with a ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1125806", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000131335.jpg", "positive_caption": ["people walking on a street with a clock on a building"], "negative_caption": ["people walking on a street with a book on a building"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1269341", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000439007.jpg", "positive_caption": ["a polar bear fully submerged in a small body of water"], "negative_caption": ["a polar bird fully submerged in a small body of water"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1123561", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000124416.jpg", "positive_caption": ["a woman on a red surfboard looking away from the camera"], "negative_caption": ["a woman on a red snowboard looking away from the camera"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1178379", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000299734.jpg", "positive_caption": ["two men in a grassy field playing with a frisbee."], "negative_caption": ["two men in a grassy field playing with a ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1236677", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000405261.jpg", "positive_caption": ["two people eating rolls and food in a black bowl."], "negative_caption": ["two people eating rolls and food in a black knife."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1012404", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000162914.jpg", "positive_caption": ["a clock hanging from rafters of a building"], "negative_caption": ["a book hanging from rafters of a building"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1075513", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000528595.jpg", "positive_caption": ["a group of people ride on a very small train."], "negative_caption": ["a group of people ride on a very small truck."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1115214", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000501047.jpg", "positive_caption": ["a single elephant that is walking in a field."], "negative_caption": ["a single horse that is walking in a field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1071546", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000236865.jpg", "positive_caption": ["a small girl in a flowered dress watches a frisbee"], "negative_caption": ["a small girl in a flowered dress watches a ball"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1123723", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000528276.jpg", "positive_caption": ["a man riding a skateboard down a walk way."], "negative_caption": ["a man riding a kite down a walk way."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1049289", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000215151.jpg", "positive_caption": ["a man flying through the air while riding a skateboard."], "negative_caption": ["a man flying through the air while riding a frisbee."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1083077", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000055017.jpg", "positive_caption": ["a sandwich with turkey, avocado, tomatoes and lettuce with french fries aside."], "negative_caption": ["a pizza with turkey, avocado, tomatoes and lettuce with french fries aside."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1193519", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000151521.jpg", "positive_caption": ["a large group of people are sitting at a table together."], "negative_caption": ["a large group of people are sitting at a bed together."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1149499", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000476035.jpg", "positive_caption": ["a crowd of people standing around a table with pizza on it."], "negative_caption": ["a crowd of people standing around a table with sandwich on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1125679", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000020925.jpg", "positive_caption": ["a young woman making a face while working on a laptop."], "negative_caption": ["a young woman making a face while working on a tv."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1187443", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000165257.jpg", "positive_caption": ["a large black counter top sitting next to a sink."], "negative_caption": ["a large black counter top sitting next to a refrigerator."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1059880", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000069106.jpg", "positive_caption": ["a herd of zebra standing next to each other against a stone wall."], "negative_caption": ["a herd of elephant standing next to each other against a stone wall."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1033452", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000117525.jpg", "positive_caption": ["a man in a red santa hat and a dog pose in front of a christmas tree."], "negative_caption": ["a man in a red santa hat and a horse pose in front of a christmas tree."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1159124", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000193114.jpg", "positive_caption": ["a brick tower with a clock built in the side of it"], "negative_caption": ["a brick tower with a scissors built in the side of it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1270335", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000451345.jpg", "positive_caption": ["a lady sitting on a concrete picnic table"], "negative_caption": ["a lady sitting on a concrete picnic chair"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1044684", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000177323.jpg", "positive_caption": ["a cat laying on its back with something around its neck"], "negative_caption": ["a dog laying on its back with something around its neck"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1159946", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000447596.jpg", "positive_caption": ["a hotel bathroom with a blue sink and white towels"], "negative_caption": ["a hotel bathroom with a blue refrigerator and white towels"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1106273", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000098043.jpg", "positive_caption": ["a man is posing in front of his motorcycle."], "negative_caption": ["a man is posing in front of his bicycle."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1219003", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000307531.jpg", "positive_caption": ["a tan dog running in the grass after a frisbee"], "negative_caption": ["a tan bear running in the grass after a frisbee"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1236979", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000513724.jpg", "positive_caption": ["a large elephant with its face and neck decorated at an event"], "negative_caption": ["a large horse with its face and neck decorated at an event"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1191875", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000367228.jpg", "positive_caption": ["young man flying a kite over a grassy area by water."], "negative_caption": ["young man flying a frisbee over a grassy area by water."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1261588", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000462802.jpg", "positive_caption": ["a see through vase with flowers sits in front of a window"], "negative_caption": ["a see through clock with flowers sits in front of a window"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1171734", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000034141.jpg", "positive_caption": ["a large adult giraffe standing in tall grass near trees."], "negative_caption": ["a large adult zebra standing in tall grass near trees."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1271869", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000513789.jpg", "positive_caption": ["a bed sitting in a bedroom under a window."], "negative_caption": ["a couch sitting in a bedroom under a window."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1170314", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000528200.jpg", "positive_caption": ["a black vase with a couple of flowers sticking out from it."], "negative_caption": ["a black clock with a couple of flowers sticking out from it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1165016", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000314607.jpg", "positive_caption": ["a tower clock on top of the building in the city"], "negative_caption": ["a tower scissors on top of the building in the city"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1097900", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000085956.jpg", "positive_caption": ["a yellow double decker bus driving under a bridge."], "negative_caption": ["a yellow double decker airplane driving under a bridge."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1279307", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000450370.jpg", "positive_caption": ["a baby elephant walking through a forest next to trees."], "negative_caption": ["a baby horse walking through a forest next to trees."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1018000", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000184762.jpg", "positive_caption": ["a close up of the clock face of a grandfather clock."], "negative_caption": ["a close up of the clock face of a grandfather scissors."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1114001", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000027519.jpg", "positive_caption": ["a man with his dog on a leash talking to another man"], "negative_caption": ["a man with his horse on a leash talking to another man"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1203305", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000194559.jpg", "positive_caption": ["a bed with several items of cloth arranged as hearts on top."], "negative_caption": ["a table with several items of cloth arranged as hearts on top."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1118720", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000548275.jpg", "positive_caption": ["a bird is perched on a rock in the sea water."], "negative_caption": ["a cat is perched on a rock in the sea water."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1069305", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000040705.jpg", "positive_caption": ["a man looks seriously into the camera and is wearing a blue and black striped shirt and a polka dot tie."], "negative_caption": ["a man looks seriously into the camera and is wearing a blue and black striped shirt and a polka dot suitcase."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1243296", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000282150.jpg", "positive_caption": ["the motorcycle is equipped with all the latest gadgets."], "negative_caption": ["the car is equipped with all the latest gadgets."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1135513", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000057363.jpg", "positive_caption": ["a fire truck (ladder truck) drives down a street in the city."], "negative_caption": ["a fire truck (ladder motorcycle) drives down a street in the city."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1250478", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000233311.jpg", "positive_caption": ["a stuffed animal sitting on a table, with oranges behind it."], "negative_caption": ["a stuffed animal sitting on a bed, with oranges behind it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1038172", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000367666.jpg", "positive_caption": ["a cell phone in a holder attached to a desk"], "negative_caption": ["a cell keyboard in a holder attached to a desk"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1105244", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000558449.jpg", "positive_caption": ["a terra cotta pot containing white and orange flowers."], "negative_caption": ["a terra cotta pot containing white and carrot flowers."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1022493", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000334466.jpg", "positive_caption": ["a giraffe eating leaves off a skinny tree."], "negative_caption": ["a zebra eating leaves off a skinny tree."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1054240", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000229946.jpg", "positive_caption": ["a tusked elephant and a baby elephant walking into a lake"], "negative_caption": ["a tusked elephant and a baby zebra walking into a lake"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1183220", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000419473.jpg", "positive_caption": ["a stove holding a large pizza covered in cheese and meatballs."], "negative_caption": ["a stove holding a large sandwich covered in cheese and meatballs."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1186624", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000461751.jpg", "positive_caption": ["the man is riding his motorcycle while smoking a cigarette."], "negative_caption": ["the man is riding his bicycle while smoking a cigarette."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1082956", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000301380.jpg", "positive_caption": ["sheep graze peacefully in a field near the water."], "negative_caption": ["cow graze peacefully in a field near the water."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1092516", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000576714.jpg", "positive_caption": ["a white sheep in grassy area with trees in background."], "negative_caption": ["a white cow in grassy area with trees in background."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1272367", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000504902.jpg", "positive_caption": ["a black truck with dog kennel on its bed and dogs in field."], "negative_caption": ["a black truck with horse kennel on its bed and dogs in field."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1212599", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000463802.jpg", "positive_caption": ["a stuffed animal watching an excited tennis player on tv."], "negative_caption": ["a stuffed animal watching an excited tennis player on phone."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1103980", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000554579.jpg", "positive_caption": ["three women wearing long dresses standing behind a dog."], "negative_caption": ["three women wearing long dresses standing behind a horse."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1251260", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000572935.jpg", "positive_caption": ["a giraffe turns it head on the savannah with trees in the background."], "negative_caption": ["a horse turns it head on the savannah with trees in the background."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1211723", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000091488.jpg", "positive_caption": ["his is a herd of sheep on the side of a mountain"], "negative_caption": ["his is a herd of giraffe on the side of a mountain"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1234366", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000220699.jpg", "positive_caption": ["a smart phone sitting on a cloth next to a battery hooked up to another device."], "negative_caption": ["a smart laptop sitting on a cloth next to a battery hooked up to another device."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1179921", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000278435.jpg", "positive_caption": ["man and dog on scooter in city street on sunny day."], "negative_caption": ["man and horse on scooter in city street on sunny day."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1226058", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000101265.jpg", "positive_caption": ["a big bear plays with another bears neck"], "negative_caption": ["a big cat plays with another bears neck"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1266788", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000293802.jpg", "positive_caption": ["a boy performing a kickflip on his skateboard on a city street."], "negative_caption": ["a boy performing a kickflip on his frisbee on a city street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1000080", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000376531.jpg", "positive_caption": ["a little kid throwing a ball while holding a bat"], "negative_caption": ["a little kid throwing a ball while holding a kite"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1058864", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000556183.jpg", "positive_caption": ["a noodle dish has alfredo sauce, broccoli, and mushrooms."], "negative_caption": ["a noodle dish has alfredo sauce, carrot, and mushrooms."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1124434", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000528866.jpg", "positive_caption": ["a glass plate filled with lots of vegetables."], "negative_caption": ["a fork plate filled with lots of vegetables."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1200163", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000326308.jpg", "positive_caption": ["a vase full of pink flowers with a black background."], "negative_caption": ["a clock full of pink flowers with a black background."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1225441", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000372855.jpg", "positive_caption": ["a bear walks around a man made pool"], "negative_caption": ["a bird walks around a man made pool"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1289825", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000481890.jpg", "positive_caption": ["large white teddy bear laying fave down on a bed."], "negative_caption": ["large white teddy bear laying fave down on a couch."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1289568", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000387074.jpg", "positive_caption": ["a man riding a surfboard on a small wave in the ocean."], "negative_caption": ["a man riding a snowboard on a small wave in the ocean."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1296976", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000236925.jpg", "positive_caption": ["a zebra on the road walking pass a car."], "negative_caption": ["a cat on the road walking pass a car."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1296243", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000384981.jpg", "positive_caption": ["the cake is decorated for the family celebration."], "negative_caption": ["the pizza is decorated for the family celebration."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1012525", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000372874.jpg", "positive_caption": ["a close up of a dog riding a skate board"], "negative_caption": ["a close up of a horse riding a skate board"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1048081", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000261175.jpg", "positive_caption": ["a home kitchen with wood cabinets and a long table"], "negative_caption": ["a home kitchen with wood cabinets and a long bed"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1188115", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000161642.jpg", "positive_caption": ["an image of clock that is on the wall"], "negative_caption": ["an image of scissors that is on the wall"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1187470", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000168817.jpg", "positive_caption": ["a cat laying down with its head on a remote control."], "negative_caption": ["a dog laying down with its head on a remote control."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1137557", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000104185.jpg", "positive_caption": ["a batter is taking a swing at the ball."], "negative_caption": ["a batter is taking a swing at the glove."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1187041", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000446117.jpg", "positive_caption": ["an orange sitting on top of a wooden table"], "negative_caption": ["an apple sitting on top of a wooden table"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1264120", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000429261.jpg", "positive_caption": ["there is a sandwich and sides on a tray on the table."], "negative_caption": ["there is a pizza and sides on a tray on the table."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1207784", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000508087.jpg", "positive_caption": ["a truck with a huge pile of banana stalks with a political painting on it."], "negative_caption": ["a truck with a huge pile of broccoli stalks with a political painting on it."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1139240", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000122172.jpg", "positive_caption": ["a baby elephant walk next to some adult elephants"], "negative_caption": ["a baby zebra walk next to some adult elephants"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1168327", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000358103.jpg", "positive_caption": ["a bathroom with a plant and vase in window."], "negative_caption": ["a bathroom with a plant and clock in window."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1052494", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000005245.jpg", "positive_caption": ["a man in a canoe boat in the back of a elephant"], "negative_caption": ["a man in a canoe truck in the back of a elephant"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1198136", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000118811.jpg", "positive_caption": ["a child sits at a table with plates and glasses."], "negative_caption": ["a child sits at a chair with plates and glasses."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1200898", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000203110.jpg", "positive_caption": ["an orange trolley traveling down a city street."], "negative_caption": ["an apple trolley traveling down a city street."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1212180", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000018014.jpg", "positive_caption": ["a pizza with peppers, tomatoes, chicken and cheese."], "negative_caption": ["a sandwich with peppers, tomatoes, chicken and cheese."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1216041", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000111683.jpg", "positive_caption": ["two men in black dress clothing eating food off of a table."], "negative_caption": ["two men in black dress clothing eating food off of a chair."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1108545", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000312204.jpg", "positive_caption": ["a large gray elephant walking through a lush green forest."], "negative_caption": ["a large gray horse walking through a lush green forest."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1160644", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000134649.jpg", "positive_caption": ["a white toilet sitting under a bathroom window."], "negative_caption": ["a white bed sitting under a bathroom window."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1007746", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000115875.jpg", "positive_caption": ["a little girl sitting on the floor holding a wii remote"], "negative_caption": ["a little girl sitting on the floor holding a wii laptop"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1224214", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000480951.jpg", "positive_caption": ["car headlights and brake lights in x form with night view"], "negative_caption": ["bicycle headlights and brake lights in x form with night view"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1128791", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000374051.jpg", "positive_caption": ["a woman on a tennis court holding a tennis racket."], "negative_caption": ["a woman on a tennis court holding a tennis ball."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1097350", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000348708.jpg", "positive_caption": ["a bowl with something in it with a banana next to it"], "negative_caption": ["a bottle with something in it with a banana next to it"], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1023839", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000350405.jpg", "positive_caption": ["a man riding a snowboard down a ski slope."], "negative_caption": ["a man riding a kite down a ski slope."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1185156", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000428554.jpg", "positive_caption": ["a man in a leans forward and ties a bow tie."], "negative_caption": ["a man in a leans forward and ties a bow suitcase."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1243143", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000370478.jpg", "positive_caption": ["corner of a bedroom with a laptop and luggage on a floor."], "negative_caption": ["corner of a bedroom with a tv and luggage on a floor."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1160521", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000567863.jpg", "positive_caption": ["a tall giraffe standing next to a baby giraffe."], "negative_caption": ["a tall giraffe standing next to a baby zebra."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1143235", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "FOIL/COCO_val2014_000000232115.jpg", "positive_caption": ["a four tiered dessert plate full of dessert on a table outside."], "negative_caption": ["a four tiered dessert plate full of dessert on a chair outside."], "original_file_name": "foil-it", "dataset": "FOIL dataset", "key": "1049305", "linguistic_phenomena": "noun phrases", "original_split": "test"}
{"image_file_name": "coco2017/000000291619.jpg", "positive_caption": ["Two young men playing frisbee at night on exactly one sports field"], "negative_caption": ["Two young men playing frisbee at night on a number of sports fields"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:308510", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000455716.jpg", "positive_caption": ["Exactly one row of motorcycles parked together on a grass yard area with a house in the background."], "negative_caption": ["A number of rows of motorcycles parked together on a grass yard area with a house in the background."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:295305", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000500565.jpg", "positive_caption": ["A woman is holding a baby who is wrapped in exactly one towel and holding a toothbrush"], "negative_caption": ["A woman is holding a baby who is wrapped in a number of towels and holding a toothbrush"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:286302", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000295316.jpg", "positive_caption": ["Some people are riding surfboards on exactly one wave"], "negative_caption": ["Some people are riding surfboards on a number of waves"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:753503", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000336356.jpg", "positive_caption": ["The woman is sitting at a single table and eating pizza."], "negative_caption": ["The woman is sitting at some tables and eating pizza."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:534979", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000521601.jpg", "positive_caption": ["A chocolate candy is at exactly one bottom of a cup."], "negative_caption": ["A chocolate candy is at some bottoms of a cup."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:315846", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000132375.jpg", "positive_caption": ["A glass vase with three pink flowers and a single drink"], "negative_caption": ["A glass vase with three pink flowers and some drinks"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:566653", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000153217.jpg", "positive_caption": ["A cat walks next to exactly one motorcycle on a sidewalk."], "negative_caption": ["A cat walks next to a number of motorcycles on a sidewalk."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:82901", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000167902.jpg", "positive_caption": ["Exactly one colorful toucan perched on a branch in some trees."], "negative_caption": ["A number of colorful toucans perched on a branch in some trees."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:167377", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000336053.jpg", "positive_caption": ["Two children enjoy a meal at a single restaurant."], "negative_caption": ["Two children enjoy a meal at some restaurants."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:301260", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000239773.jpg", "positive_caption": ["Exactly one baseball player is about to swing at the ball."], "negative_caption": ["A number of baseball players are about to swing at the ball."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:474488", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000029640.jpg", "positive_caption": ["A skillet contains exactly one diced meat and mixed vegetables."], "negative_caption": ["A skillet contains a number of diced meats and mixed vegetables."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:564468", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000017029.jpg", "positive_caption": ["A dog catches a single frisbee outside in the grass."], "negative_caption": ["A dog catches some frisbees outside in the grass."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:782283", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000389684.jpg", "positive_caption": ["A man is walking down a single sidewalk next to a bus on the street"], "negative_caption": ["A man is walking down a number of sidewalks next to a bus on the street"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:392490", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000084674.jpg", "positive_caption": ["Exactly one girl holds a baby eating a bagel with a boy standing next to them"], "negative_caption": ["Some girls hold a baby eating a bagel with a boy standing next to them"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:75000", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000099182.jpg", "positive_caption": ["A man in a black jacket is flipping through exactly one large book."], "negative_caption": ["A man in a black jacket is flipping through a number of large books."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:581496", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000245320.jpg", "positive_caption": ["A man riding exactly one skateboard down a cement ramp."], "negative_caption": ["A man riding a number of skateboards down a cement ramp."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:729815", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000180188.jpg", "positive_caption": ["Exactly one freightliner sits on the tracks with graffiti spray - painted on the side."], "negative_caption": ["Some freightliners sit on the tracks with graffiti spray - painted on the side."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:662426", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000509699.jpg", "positive_caption": ["A single person on a flowered chair is watching an old television."], "negative_caption": ["Some people on a flowered chair are watching an old television."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:182831", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000174231.jpg", "positive_caption": ["Exactly one cat is laying inside of a half open lap top."], "negative_caption": ["Some cats are laying inside of a half open lap top."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:527671", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000222458.jpg", "positive_caption": ["A woman in exactly one coat walks along a snow covered sidewalk."], "negative_caption": ["A woman in a number of coats walks along a snow covered sidewalk."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:83831", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000055299.jpg", "positive_caption": ["A bird is perched on exactly one large rock near the shore."], "negative_caption": ["A bird is perched on a number of large rocks near the shore."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:572841", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000502168.jpg", "positive_caption": ["The men wear hardhats as they work on a single aircraft carrier."], "negative_caption": ["The men wear hardhats as they work on a number of aircraft carriers."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:352627", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000462904.jpg", "positive_caption": ["There is exactly one small black pony in the sand"], "negative_caption": ["There are a number of small black ponies in the sand"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:336961", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000197388.jpg", "positive_caption": ["Cross country skiers travel through the snow during exactly one race."], "negative_caption": ["Cross country skiers travel through the snow during a number of races."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:44026", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000039951.jpg", "positive_caption": ["A boy is hitting a tennis ball on a single tennis court."], "negative_caption": ["A boy is hitting a tennis ball on some tennis courts."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:508734", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000428218.jpg", "positive_caption": ["A man and exactly one woman are playing outside."], "negative_caption": ["A man and a number of women are playing outside."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:495800", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000194875.jpg", "positive_caption": ["A line of neon colored motorcycles parked in front of exactly one bar."], "negative_caption": ["A line of neon colored motorcycles parked in front of a number of bars."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:194475", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000067310.jpg", "positive_caption": ["A young man skateboarding jumps on a single concrete ramp."], "negative_caption": ["A young man skateboarding jumps on a number of concrete ramps."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:653930", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000194746.jpg", "positive_caption": ["There is a pizza in a single oven that has melted onto the bottom."], "negative_caption": ["There is a pizza in some ovens that has melted onto the bottom."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:86131", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000016228.jpg", "positive_caption": ["A single horse pulling a wagon with a conductor down the road."], "negative_caption": ["A number of horses pulling a wagon with a conductor down the road."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:500354", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000038118.jpg", "positive_caption": ["The man is skiing down exactly one snowy hill."], "negative_caption": ["The man is skiing down some snowy hills."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:450604", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000105264.jpg", "positive_caption": ["Exactly one bull is running freely on the beach with other boys."], "negative_caption": ["Some bulls are running freely on the beach with other boys."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:723804", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000497344.jpg", "positive_caption": ["A baby has one hand on a computer and holds a single cellphone in the other hand."], "negative_caption": ["A baby has one hand on a computer and holds a number of cellphones in the other hand."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:178720", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000567886.jpg", "positive_caption": ["A single student is trying to relax on the floor."], "negative_caption": ["A number of students are trying to relax on the floor."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:363954", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000082812.jpg", "positive_caption": ["A group of people wait for exactly one subway."], "negative_caption": ["A group of people wait for a number of subways."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:120633", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000132544.jpg", "positive_caption": ["A girl attempts to hit exactly one ball with her bat while playing baseball."], "negative_caption": ["A girl attempts to hit a number of balls with her bat while playing baseball."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:49369", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000180751.jpg", "positive_caption": ["A man pouring exactly one drink into a wine glass"], "negative_caption": ["A man pouring some drinks into a wine glass"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:690170", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000361919.jpg", "positive_caption": ["Many skiers are walking and skiing around exactly one snow."], "negative_caption": ["Many skiers are walking and skiing around a number of snows."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:178418", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000014473.jpg", "positive_caption": ["Exactly one red and black train is coming down the tracks"], "negative_caption": ["A number of red and black trains are coming down the tracks"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:645971", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000181542.jpg", "positive_caption": ["A woman in white crosses exactly one road against the flow of motorcycle traffic."], "negative_caption": ["A woman in white crosses some roads against the flow of motorcycle traffic."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:581736", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000563653.jpg", "positive_caption": ["Exactly one quiet city street shows buildings, cars, and people."], "negative_caption": ["Some quiet city streets show buildings, cars, and people."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:183368", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000560911.jpg", "positive_caption": ["A single man sits on a couch holding his phone."], "negative_caption": ["Some men sit on a couch holding their phones."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:823283", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000488673.jpg", "positive_caption": ["A single man and woman are in a kitchen."], "negative_caption": ["A number of men and woman are in a kitchen."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:459575", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000474344.jpg", "positive_caption": ["A man holds a bat while a single woman watches."], "negative_caption": ["A man holds a bat while some women watch."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:661402", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000089697.jpg", "positive_caption": ["Exactly one couple of people are sitting on a wood bench"], "negative_caption": ["A number of couples of people are sitting on a wood bench"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:686499", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000244099.jpg", "positive_caption": ["Exactly one person is riding a horse that is running very fast"], "negative_caption": ["A number of people are riding a horse that is running very fast"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:599646", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000548339.jpg", "positive_caption": ["A man is swinging at a ball during exactly one baseball game."], "negative_caption": ["A man is swinging at a ball during some baseball games."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:428691", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000495146.jpg", "positive_caption": ["People are in exactly one parking lot   beside the water, while a train is in the background."], "negative_caption": ["People are in a number of parking lots beside the water, while a train is in the background."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:94317", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000110972.jpg", "positive_caption": ["Exactly one black bear is standing outdoors in the wild."], "negative_caption": ["A number of black bears are standing outdoors in the wild."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:640784", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000437351.jpg", "positive_caption": ["Exactly one young woman sits near three suitcases of luggage."], "negative_caption": ["A number of young women sit near three suitcases of luggage."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:203565", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000523782.jpg", "positive_caption": ["Exactly one bird is sitting on a silver truck"], "negative_caption": ["Some birds are sitting on a silver truck"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:171289", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000312278.jpg", "positive_caption": ["A single rack filled with lots of different bags of luggage."], "negative_caption": ["A number of racks filled with lots of different bags of luggage."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:380938", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000070774.jpg", "positive_caption": ["A single motorcycle parked outside of a building with bird cages."], "negative_caption": ["Some motorcycles parked outside of a building with bird cages."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:200963", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000275392.jpg", "positive_caption": ["The child sits on a single horse in the pasture."], "negative_caption": ["The child sits on a number of horses in the pasture."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:9183", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000382030.jpg", "positive_caption": ["A cluttered collection of various items including a wig, shoes, exactly one umbrella and a photo."], "negative_caption": ["A cluttered collection of various items including a wig, shoes, some umbrellas and a photo."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:229432", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000263463.jpg", "positive_caption": ["Exactly one dog sticks his head out of a car window."], "negative_caption": ["A number of dogs stick their heads out of a car window."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:357038", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000300233.jpg", "positive_caption": ["The ingredients are on the kitchen counter next to exactly one blender."], "negative_caption": ["The ingredients are on the kitchen counter next to a number of blenders."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:283831", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000461751.jpg", "positive_caption": ["Exactly one man is riding a motorcycle on a city street."], "negative_caption": ["A number of men are riding a motorcycle on a city street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:670436", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000082696.jpg", "positive_caption": ["A white and black bird is walking by exactly one table and some chairs"], "negative_caption": ["A white and black bird is walking by a number of tables and some chairs"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:84476", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000484760.jpg", "positive_caption": ["A statue of a single woman holding a ball stands in front of the old church."], "negative_caption": ["A statue of some women holding a ball stands in front of the old church."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:492577", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000226417.jpg", "positive_caption": ["Several motorcycles are parked at a red light in the road in a single city with tall buildings."], "negative_caption": ["Several motorcycles are parked at a red light in the road in a number of cities with tall buildings."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:501300", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000072813.jpg", "positive_caption": ["A cute brown puppy is snuggled on exactly one rumpled bed."], "negative_caption": ["A cute brown puppy is snuggled on a number of rumpled beds."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:633094", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000161032.jpg", "positive_caption": ["A woman in a sheer dress leans down while holding exactly one umbrella."], "negative_caption": ["A woman in a sheer dress leans down while holding some umbrellas."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:70174", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000150726.jpg", "positive_caption": ["Two giraffes are walking abreast on exactly one grassy field."], "negative_caption": ["Two giraffes are walking abreast on some grassy fields."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:301635", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000030828.jpg", "positive_caption": ["A person is sleeping on a single bench in a sleeping bag."], "negative_caption": ["A person is sleeping on a number of benches in a sleeping bag."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:158251", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000297681.jpg", "positive_caption": ["A car is driving through exactly one flooded street."], "negative_caption": ["A car is driving through a number of flooded streets."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:766438", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000473118.jpg", "positive_caption": ["A skateboarder is turning his board at the top of exactly one ramp"], "negative_caption": ["A skateboarder is turning his board at the top of some ramps"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:101488", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000218362.jpg", "positive_caption": ["A large digital clock mounted to a single wall."], "negative_caption": ["A large digital clock mounted to a number of walls."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:233194", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000014380.jpg", "positive_caption": ["The white bridge stretches out over the horizon as a single transport train travels below it."], "negative_caption": ["The white bridge stretches out over the horizon as a number of transport trains travel below it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:53684", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000344795.jpg", "positive_caption": ["Exactly one oven contains a dish that is covered with tin foil."], "negative_caption": ["A number of ovens contain a dish that is covered with tin foil."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:465921", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000038048.jpg", "positive_caption": ["A red fire hydrant is on exactly one sidewalk next to a sign."], "negative_caption": ["A red fire hydrant is on a number of sidewalks next to a sign."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:380741", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000125072.jpg", "positive_caption": ["Cows graze a single open field next to the ocean."], "negative_caption": ["Cows graze a number of open fields next to the ocean."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:66572", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000327617.jpg", "positive_caption": ["A vintage photo of a woman with a single tennis racket"], "negative_caption": ["A vintage photo of a woman with some tennis rackets"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:443877", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000087144.jpg", "positive_caption": ["A man and a single woman sit on benches with a small child."], "negative_caption": ["A man and a number of women sit on benches with a small child."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:42454", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000297698.jpg", "positive_caption": ["Exactly one man is skiing in mid jump onto a ramp."], "negative_caption": ["A number of men are skiing in mid jump onto a ramp."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:732974", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000325838.jpg", "positive_caption": ["A woman works at a computer workstation in exactly one office."], "negative_caption": ["A woman works at a computer workstation in some offices."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:694092", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000579900.jpg", "positive_caption": ["A delicious looking pizza with a variety of vegetable toppings stands out on exactly one yellow plate."], "negative_caption": ["A delicious looking pizza with a variety of vegetable toppings stands out on a number of yellow plates."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:197139", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000345941.jpg", "positive_caption": ["A dessert topped with ice cream, and strawberries sits on exactly one plate."], "negative_caption": ["A dessert topped with ice cream, and strawberries sits on a number of plates."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:745184", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000412894.jpg", "positive_caption": ["Dozens of people walking around exactly one metro area"], "negative_caption": ["Dozens of people walking around a number of metro areas"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:60806", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000331799.jpg", "positive_caption": ["The woman is handing a single package to another person."], "negative_caption": ["The woman is handing some packages to another person."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:730662", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000064898.jpg", "positive_caption": ["Two surfers paddle back to a single beach on their surfboards."], "negative_caption": ["Two surfers paddle back to a number of beaches on their surfboards."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:321001", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000422836.jpg", "positive_caption": ["A single man is holding a suitcase at a city intersection."], "negative_caption": ["Some men are holding a suitcase at a city intersection."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:17502", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000578093.jpg", "positive_caption": ["A large train is sitting inside exactly one train station"], "negative_caption": ["A large train is sitting inside some train stations"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:431243", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000477805.jpg", "positive_caption": ["A man types quickly on exactly one laptop at night."], "negative_caption": ["A man types quickly on a number of laptops at night."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:87401", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000263425.jpg", "positive_caption": ["Two men are looking inside of a single giant barbecue."], "negative_caption": ["Two men are looking inside of a number of giant barbecues."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:381743", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000476415.jpg", "positive_caption": ["A single person stands and shows his tie off."], "negative_caption": ["Some people stand and shows their ties off."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:160187", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000261712.jpg", "positive_caption": ["Two giraffes wander exactly one open park in the same direction."], "negative_caption": ["Two giraffes wander a number of open parks in the same direction."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:151030", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000509131.jpg", "positive_caption": ["The over ripe bananas are hanging from exactly one stand."], "negative_caption": ["The over ripe bananas are hanging from some stands."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:61001", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000342128.jpg", "positive_caption": ["A man is holding exactly one tennis racket while posing."], "negative_caption": ["A man is holding a number of tennis rackets while posing."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:634058", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000236914.jpg", "positive_caption": ["Two stuffed animals sit at a table with exactly one honey."], "negative_caption": ["Two stuffed animals sit at a table with a number of honeys."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:51692", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000573391.jpg", "positive_caption": ["A bear is walking on an unpaved path in a single wilderness area."], "negative_caption": ["A bear is walking on an unpaved path in some wilderness areas."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:294109", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000174004.jpg", "positive_caption": ["A single yellow truck is sitting in high grass."], "negative_caption": ["Some yellow trucks are sitting in high grass."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:182438", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000165039.jpg", "positive_caption": ["A bus pulls over to the curb close to exactly one intersection."], "negative_caption": ["A bus pulls over to the curb close to some intersections."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:605539", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000462614.jpg", "positive_caption": ["Exactly one bathroom has red walls with yellow accents."], "negative_caption": ["Some bathrooms have red walls with yellow accents."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:206739", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000270908.jpg", "positive_caption": ["There is a single tennis player laying down on the court"], "negative_caption": ["There are a number of tennis players laying down on the court"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:119166", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000167128.jpg", "positive_caption": ["A couple of elephants walk as a single baby walks next to them"], "negative_caption": ["A couple of elephants walk as some babies walk next to them"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:434735", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000324818.jpg", "positive_caption": ["Exactly one couple of birds are standing on a branch"], "negative_caption": ["Some couples of birds are standing on a branch"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:583642", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000425221.jpg", "positive_caption": ["Exactly one plane is flying away from the airport"], "negative_caption": ["Some planes are flying away from the airport"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:101633", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000383676.jpg", "positive_caption": ["Two giraffes stand near rocks in a single zoo."], "negative_caption": ["Two giraffes stand near rocks in some zoos."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:595224", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000355817.jpg", "positive_caption": ["Exactly one bus parked in front of a brick building."], "negative_caption": ["Some buses parked in front of a brick building."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:272250", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000162415.jpg", "positive_caption": ["The girl with exactly one baseball mitt is smiling."], "negative_caption": ["The girl with a number of baseball mitts is smiling."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:729868", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000348216.jpg", "positive_caption": ["A dim room with toilet bowls lined along exactly one wall"], "negative_caption": ["A dim room with toilet bowls lined along a number of walls"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:642286", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000140439.jpg", "positive_caption": ["A clear vase sits on exactly one table and holds long stemmed tulips."], "negative_caption": ["A clear vase sits on a number of tables and holds long stemmed tulips."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:188667", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000257370.jpg", "positive_caption": ["Two people playing exactly one video game on a television."], "negative_caption": ["Two people playing a number of video games on a television."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:167211", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000417465.jpg", "positive_caption": ["A large black bear with exactly one long tongue hanging out of it's mouth."], "negative_caption": ["A large black bear with a number of long tongues hanging out of it's mouth."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:97961", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000210230.jpg", "positive_caption": ["The woman is putting a single hot dog into the bun."], "negative_caption": ["The woman is putting some hot dogs into the bun."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:579717", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000201072.jpg", "positive_caption": ["A single man in white is playing on a tennis court."], "negative_caption": ["A number of men in white are playing on a tennis court."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:689740", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000513041.jpg", "positive_caption": ["A single peeson at a table is eating a small pizza"], "negative_caption": ["Some peesons at a table are eating a small pizza"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:222360", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000280918.jpg", "positive_caption": ["Two women are taking a turkey out of exactly one oven."], "negative_caption": ["Two women are taking a turkey out of a number of ovens."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:205903", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000456662.jpg", "positive_caption": ["A single little girl is standing in front of a refrigerator."], "negative_caption": ["Some little girls are standing in front of a refrigerator."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:346716", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000378873.jpg", "positive_caption": ["Fruits and vegetables are being sold in a single market."], "negative_caption": ["Fruits and vegetables are being sold in a number of markets."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:145149", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000227765.jpg", "positive_caption": ["The meal is being prepared in a single big pot."], "negative_caption": ["The meal is being prepared in some big pots."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:391255", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000122927.jpg", "positive_caption": ["Two adult pheasants walking slowly across exactly one street"], "negative_caption": ["Two adult pheasants walking slowly across some streets"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:102942", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000577976.jpg", "positive_caption": ["Exactly one construction truck is in front of the huge building."], "negative_caption": ["A number of construction trucks are in front of the huge building."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:623401", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000357567.jpg", "positive_caption": ["A bathroom with a single toilet and a blue striped shower curtain."], "negative_caption": ["A bathroom with some toilets and a blue striped shower curtain."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:149786", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000431568.jpg", "positive_caption": ["A large pizza is on exactly one white plate"], "negative_caption": ["A large pizza is on some white plates"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:810427", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000277197.jpg", "positive_caption": ["A single very large and very posh living room."], "negative_caption": ["A number of very large and very posh living rooms."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:288587", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000485895.jpg", "positive_caption": ["Exactly one small giraffe stands in the grass near a road."], "negative_caption": ["Some small giraffes stand in the grass near a road."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:183280", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000494759.jpg", "positive_caption": ["Two people fly a kite on exactly one beach."], "negative_caption": ["Two people fly a kite on a number of beaches."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:59317", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000036494.jpg", "positive_caption": ["A bunch of people gathered inside of exactly one building"], "negative_caption": ["A bunch of people gathered inside of some buildings"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:641154", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000564280.jpg", "positive_caption": ["A dog is sitting on exactly one couch by a remote."], "negative_caption": ["A dog is sitting on a number of couches by a remote."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:362292", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000372260.jpg", "positive_caption": ["A car is parked near a clock that is surrounded by flowers at a single bottom of the pole."], "negative_caption": ["A car is parked near a clock that is surrounded by flowers at some bottoms of the pole."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:267801", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000403584.jpg", "positive_caption": ["Two surfers stand with their surfboards on a single beach."], "negative_caption": ["Two surfers stand with their surfboards on some beaches."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:184755", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000080932.jpg", "positive_caption": ["A little boy sits at a table in a restaurant eating a single slice of pizza."], "negative_caption": ["A little boy sits at a table in a restaurant eating some slices of pizza."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:505707", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000465549.jpg", "positive_caption": ["Two girls are playing video games in exactly one living room."], "negative_caption": ["Two girls are playing video games in a number of living rooms."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:629787", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000537355.jpg", "positive_caption": ["A long fire plug stands some distance away from exactly one building."], "negative_caption": ["A long fire plug stands some distance away from a number of buildings."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:210233", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000140987.jpg", "positive_caption": ["Exactly one little girl grins at her plate of pizza."], "negative_caption": ["Some little girls grin at their plates of pizza."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:225558", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000326462.jpg", "positive_caption": ["A person is holding a single doughnut with sprinkles."], "negative_caption": ["A person is holding a number of doughnuts with sprinkles."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:271527", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000327605.jpg", "positive_caption": ["A woman poses on exactly one slope with her skis."], "negative_caption": ["A woman poses on some slopes with her skis."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:760446", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000474078.jpg", "positive_caption": ["Batter punts a ball during a single baseball game."], "negative_caption": ["Batter punts a ball during a number of baseball games."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:284346", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000236592.jpg", "positive_caption": ["Exactly one dog watches something cooking in an oven."], "negative_caption": ["Some dogs watch something cooking in an oven."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:50700", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000119038.jpg", "positive_caption": ["Three white cows are standing in exactly one grassy field."], "negative_caption": ["Three white cows are standing in a number of grassy fields."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:595891", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000292225.jpg", "positive_caption": ["Two people are playing exactly one tennis in an outside court."], "negative_caption": ["Two people are playing some tenniss in an outside court."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:126344", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000009769.jpg", "positive_caption": ["A single plow truck driver is talking to his neighbor."], "negative_caption": ["A number of plow truck drivers are talking to their neighbors."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:503635", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000343524.jpg", "positive_caption": ["A man holding a tennis racquet on exactly one tennis court."], "negative_caption": ["A man holding a tennis racquet on a number of tennis courts."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:70009", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000203317.jpg", "positive_caption": ["A red bike is parked outside of a single barred window."], "negative_caption": ["A red bike is parked outside of a number of barred windows."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:395897", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000500716.jpg", "positive_caption": ["Exactly one man is wearing surgical type scissors as bifocal glasses."], "negative_caption": ["Some men are wearing surgical type scissors as bifocal glasses."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:65513", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000181969.jpg", "positive_caption": ["A single puppy all curled up taking a nap."], "negative_caption": ["Some puppies all curled up taking a nap."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:17526", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000258911.jpg", "positive_caption": ["A woman in exactly one straw hat takes photos of brown cows inside a barn."], "negative_caption": ["A woman in some straw hats takes photos of brown cows inside a barn."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:730103", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000376856.jpg", "positive_caption": ["A clock is seen at the top of exactly one very tall building."], "negative_caption": ["A clock is seen at the top of some very tall buildings."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:695705", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000254516.jpg", "positive_caption": ["A major league baseball player gets ready to hit a single ball."], "negative_caption": ["A major league baseball player gets ready to hit a number of balls."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:683848", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000201775.jpg", "positive_caption": ["A bathroom with two urinals and a single sink."], "negative_caption": ["A bathroom with two urinals and some sinks."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:29195", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000104424.jpg", "positive_caption": ["Exactly one tennis player poses with her racquet on the court"], "negative_caption": ["Some tennis players pose with their racquets on the court"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:560655", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000066135.jpg", "positive_caption": ["A train comes to exactly one stop on the tracks next to the sidewalk."], "negative_caption": ["A train comes to a number of stops on the tracks next to the sidewalk."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:533759", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000124277.jpg", "positive_caption": ["Exactly one train turns on the tracks in a different direction."], "negative_caption": ["Some trains turn on the tracks in a different direction."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:17289", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000393115.jpg", "positive_caption": ["Exactly one man has one foot on his skateboard"], "negative_caption": ["A number of men have one foot on their skateboards"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:113429", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000467511.jpg", "positive_caption": ["A biker chic in high heel boots is talking to a man at a single gas pump."], "negative_caption": ["A biker chic in high heel boots is talking to a man at some gas pumps."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:242302", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000149375.jpg", "positive_caption": ["A single person on a skateboard is doing a jump"], "negative_caption": ["Some people on a skateboard are doing a jump"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:234185", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000540466.jpg", "positive_caption": ["A woman walking by a single fence holding an orange umbrella over her"], "negative_caption": ["A woman walking by a number of fences holding an orange umbrella over her"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:296079", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000463730.jpg", "positive_caption": ["Two buses parked in a single parking lot next to cars."], "negative_caption": ["Two buses parked in a number of parking lots next to cars."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:227649", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000386277.jpg", "positive_caption": ["A single orange grows from a branch with leaves."], "negative_caption": ["A number of oranges grow from a branch with leaves."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:375701", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000168337.jpg", "positive_caption": ["There are two people standing on a single side of a street."], "negative_caption": ["There are two people standing on some sides of a street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:142653", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000562207.jpg", "positive_caption": ["A group of people are standing next to a single elephant emerging from the water."], "negative_caption": ["A group of people are standing next to some elephants emerging from the water."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:485013", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000251140.jpg", "positive_caption": ["A book about understanding and maintaining exactly one ten - speed bicycle."], "negative_caption": ["A book about understanding and maintaining some ten - speed bicycles."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:497536", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000000872.jpg", "positive_caption": ["Two men playing baseball in exactly one field on a sunny day."], "negative_caption": ["Two men playing baseball in some fields on a sunny day."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:217024", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000501368.jpg", "positive_caption": ["Exactly one person with a towel over them blow drying their hair"], "negative_caption": ["Some people with a towel over them blow drying their hair"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:315438", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000106235.jpg", "positive_caption": ["There is a cream colored couch behind a single oval coffee table."], "negative_caption": ["There is a cream colored couch behind a number of oval coffee tables."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:479887", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000068628.jpg", "positive_caption": ["A single man jumps over the steps while on his skateboard"], "negative_caption": ["A number of men jump over the steps while on their skateboards"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:513865", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000044260.jpg", "positive_caption": ["Crisp, delicious apples hang on the dying branches of a single tree."], "negative_caption": ["Crisp, delicious apples hang on the dying branches of some trees."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:291341", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000180487.jpg", "positive_caption": ["A man sits at a single table outside wearing an umbrella hat."], "negative_caption": ["A man sits at a number of tables outside wearing an umbrella hat."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:121514", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000006213.jpg", "positive_caption": ["Exactly one bathroom has two sinks, a bathtub, and a shower."], "negative_caption": ["Some bathrooms have two sinks, a bathtub, and a shower."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:826351", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000433374.jpg", "positive_caption": ["Several elephants are standing and lying on exactly one sandy beach."], "negative_caption": ["Several elephants are standing and lying on some sandy beaches."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:530098", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000368335.jpg", "positive_caption": ["A single brown horse is walking in between two cars"], "negative_caption": ["Some brown horses are walking in between two cars"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:39043", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000426166.jpg", "positive_caption": ["A bike is locked to exactly one pole in front of a red building."], "negative_caption": ["A bike is locked to some poles in front of a red building."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:505989", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000142620.jpg", "positive_caption": ["The man is sitting outside with food on a single table."], "negative_caption": ["The man is sitting outside with food on a number of tables."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:789281", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000450075.jpg", "positive_caption": ["A woman is getting her tie adjusted in a single city."], "negative_caption": ["A woman is getting her tie adjusted in some cities."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:535931", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000579655.jpg", "positive_caption": ["A woman with dark hair with a single phone to her ear"], "negative_caption": ["A woman with dark hair with some phones to her ear"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:603009", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000450399.jpg", "positive_caption": ["Exactly one store makes fresh doughnuts on site for the customers."], "negative_caption": ["A number of stores make fresh doughnuts on site for the customers."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:759827", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000508639.jpg", "positive_caption": ["The horse stands attached to a single empty carriage."], "negative_caption": ["The horse stands attached to a number of empty carriages."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:158468", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000446522.jpg", "positive_caption": ["A dog relaxes on an armchair in a single living room."], "negative_caption": ["A dog relaxes on an armchair in some living rooms."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:13418", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000061584.jpg", "positive_caption": ["A single man and woman are sitting on a statue of a horse."], "negative_caption": ["A number of men and woman are sitting on a statue of a horse."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:196518", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000346968.jpg", "positive_caption": ["Exactly one woman in uniform is talking on a cell phone."], "negative_caption": ["A number of women in uniform are talking on a cell phone."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:193116", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000293300.jpg", "positive_caption": ["There are elephants behind a fence at exactly one zoo"], "negative_caption": ["There are elephants behind a fence at a number of zoos"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:189830", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000497599.jpg", "positive_caption": ["A young man stands over a single lap top computer screen."], "negative_caption": ["A young man stands over a number of lap top computer screens."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:90803", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000041488.jpg", "positive_caption": ["Exactly one green road sign showing the queens bronx exit."], "negative_caption": ["A number of green road signs showing the queens bronx exit."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:138097", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000563470.jpg", "positive_caption": ["Exactly one young lady is playing a baseball bat game."], "negative_caption": ["A number of young ladies are playing a baseball bat game."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:491414", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000471893.jpg", "positive_caption": ["A single   image of two people playing video games"], "negative_caption": ["A number of images of two people playing video games"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:229347", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000192964.jpg", "positive_caption": ["The man is riding his skateboard down a single ramp."], "negative_caption": ["The man is riding his skateboard down a number of ramps."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:593805", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000082180.jpg", "positive_caption": ["Two stuffed animals are sitting on exactly one broken wooden chair."], "negative_caption": ["Two stuffed animals are sitting on a number of broken wooden chairs."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:64797", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000478420.jpg", "positive_caption": ["Two women in colorful dresses lean against exactly one white wall and one of them is on a cell phone."], "negative_caption": ["Two women in colorful dresses lean against some white walls and one of them is on a cell phone."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:265374", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000127394.jpg", "positive_caption": ["A group of people sit at a single table laden with food."], "negative_caption": ["A group of people sit at a number of tables laden with food."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:605611", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000427077.jpg", "positive_caption": ["A man holding exactly one baseball bat over home plate."], "negative_caption": ["A man holding a number of baseball bats over home plate."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:384084", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000493864.jpg", "positive_caption": ["A man in a single wetsuit carries a surfboard on the beach."], "negative_caption": ["A man in some wetsuits carries a surfboard on the beach."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:239154", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000157418.jpg", "positive_caption": ["A can of spam and two sandwiches sit on exactly one table."], "negative_caption": ["A can of spam and two sandwiches sit on some tables."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:113220", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000479030.jpg", "positive_caption": ["A single long red and white train travels near many other tracks."], "negative_caption": ["Some long red and white trains travel near many other tracks."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:391873", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000034873.jpg", "positive_caption": ["A large dining room features wooden cabinets and a single marble counter top."], "negative_caption": ["A large dining room features wooden cabinets and a number of marble counter tops."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:216027", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000036936.jpg", "positive_caption": ["A couple sits on a couch while playing a single wii."], "negative_caption": ["A couple sits on a couch while playing some wiis."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:727509", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000227399.jpg", "positive_caption": ["A white and gold train - style bus is parked on a single street."], "negative_caption": ["A white and gold train - style bus is parked on some streets."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:276898", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000129135.jpg", "positive_caption": ["A single bench sit in front of a blue and yellow train."], "negative_caption": ["A number of benches sit in front of a blue and yellow train."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:432343", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000149222.jpg", "positive_caption": ["Exactly one computer monitor has a framed picture near it."], "negative_caption": ["Some computer monitors have a framed picture near it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:313065", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000293804.jpg", "positive_caption": ["There is exactly one fire burning in the fireplace in a sitting room"], "negative_caption": ["There are a number of fires burning in the fireplace in a sitting room"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:724978", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000246968.jpg", "positive_caption": ["A single young woman standing in the kitchen pours from a large measuring cup."], "negative_caption": ["A number of young women standing in the kitchen pour from a large measuring cup."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:692352", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000093261.jpg", "positive_caption": ["A man prepares to fly his kite on a single sandy beach."], "negative_caption": ["A man prepares to fly his kite on some sandy beaches."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:12599", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000541291.jpg", "positive_caption": ["A single old, dilapidated bathroom has fallen into disrepair."], "negative_caption": ["A number of old, dilapidated bathrooms have fallen into disrepair."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:804991", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000237984.jpg", "positive_caption": ["Exactly one green chair is sitting behind a green bench."], "negative_caption": ["A number of green chairs are sitting behind a green bench."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:502445", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000492282.jpg", "positive_caption": ["A group of people ride horses on a single sidewalk adjacent to trees."], "negative_caption": ["A group of people ride horses on some sidewalks adjacent to trees."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:786850", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000562229.jpg", "positive_caption": ["A child wears a helmet while on exactly one skateboard"], "negative_caption": ["A child wears a helmet while on some skateboards"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:670304", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000023023.jpg", "positive_caption": ["A suitcase as well as other types of luggage are propped up on exactly one carpeted floor indoors."], "negative_caption": ["A suitcase as well as other types of luggage are propped up on a number of carpeted floors indoors."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:56817", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000399462.jpg", "positive_caption": ["Exactly one little girl is running on the grass with a kite"], "negative_caption": ["A number of little girls are running on the grass with a kite"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:538043", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000283037.jpg", "positive_caption": ["A single speed detector displays the current speed of a car"], "negative_caption": ["A number of speed detectors display the current speed of a car"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:37556", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000027186.jpg", "positive_caption": ["A single little girl is intently playing the video game."], "negative_caption": ["A number of little girls are intently playing the video game."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:773673", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000251119.jpg", "positive_caption": ["The lunchbox has exactly one cold sandwich, strawberry yogurt and orange juice."], "negative_caption": ["The lunchbox has a number of cold sandwiches, strawberry yogurt and orange juice."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:354004", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000443426.jpg", "positive_caption": ["A single man is sitting down posing for a picture."], "negative_caption": ["Some men are sitting down posing for a picture."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:666125", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000027972.jpg", "positive_caption": ["A man is surfing in exactly one crystal blue water"], "negative_caption": ["A man is surfing in a number of crystal blue waters"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:430591", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000376856.jpg", "positive_caption": ["A clock is at the top of exactly one tall brick building."], "negative_caption": ["A clock is at the top of some tall brick buildings."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:693335", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000144300.jpg", "positive_caption": ["Exactly one motorcycle parked behind two vans in a parking lot."], "negative_caption": ["A number of motorcycles parked behind two vans in a parking lot."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:639938", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000547854.jpg", "positive_caption": ["Exactly one eaten pizza is sitting on a plate"], "negative_caption": ["Some eaten pizzas are sitting on a plate"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:566343", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000200252.jpg", "positive_caption": ["Two green shoes lined up on exactly one bed."], "negative_caption": ["Two green shoes lined up on some beds."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:665263", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000445439.jpg", "positive_caption": ["Exactly one zebra is eating dry grass next to a fence."], "negative_caption": ["A number of zebras are eating dry grass next to a fence."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:216151", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000127135.jpg", "positive_caption": ["A small dog sits inside of exactly one small cart"], "negative_caption": ["A small dog sits inside of some small carts"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:362848", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000353096.jpg", "positive_caption": ["Exactly one desktop computer is sitting on a desk"], "negative_caption": ["A number of desktop computers are sitting on a desk"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:171370", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000507975.jpg", "positive_caption": ["Three horses and three jockeys are racing near a single silver car"], "negative_caption": ["Three horses and three jockeys are racing near a number of silver cars"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:723159", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000142585.jpg", "positive_caption": ["Exactly one couple of people sit on a motorcycle next to a white car."], "negative_caption": ["A number of couples of people sit on a motorcycle next to a white car."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:824086", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000439854.jpg", "positive_caption": ["A person does a trick on a skate board by exactly one beach."], "negative_caption": ["A person does a trick on a skate board by some beaches."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:385233", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000345397.jpg", "positive_caption": ["Exactly one man wearing glasses and a neck tie is holding a cell phone."], "negative_caption": ["Some men wearing glasses and a neck tie are holding a cell phone."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:380215", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000012576.jpg", "positive_caption": ["A single grandmother looks at her family's pizza dinner"], "negative_caption": ["A number of grandmothers look at their family's pizza dinners"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:174697", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000310980.jpg", "positive_caption": ["A single bear is sitting in front of a computer."], "negative_caption": ["A number of bears are sitting in front of a computer."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:807158", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000132796.jpg", "positive_caption": ["People are sitting on elephants with exactly one little chair."], "negative_caption": ["People are sitting on elephants with some little chairs."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:218709", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000320232.jpg", "positive_caption": ["Exactly one parking attendant is waiting for the fees to be paid."], "negative_caption": ["A number of parking attendants are waiting for the fees to be paid."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:463832", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000318080.jpg", "positive_caption": ["Two different bears fight with each other behind a single log"], "negative_caption": ["Two different bears fight with each other behind a number of logs"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:128933", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000477441.jpg", "positive_caption": ["Exactly one airplane sits outside, ready at the airport."], "negative_caption": ["A number of airplanes sit outside, ready at the airport."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:273200", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000535094.jpg", "positive_caption": ["A single baby cow is interested in a drink someone has."], "negative_caption": ["Some baby cows are interested in a drink someone has."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:522653", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000416269.jpg", "positive_caption": ["A single train is in the train station with the lights on."], "negative_caption": ["Some trains are in the train station with the lights on."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:763582", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000025096.jpg", "positive_caption": ["A young boy cuts exactly one cake designed to look like a skateboard."], "negative_caption": ["A young boy cuts a number of cakes designed to look like a skateboard."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:197853", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000045728.jpg", "positive_caption": ["A plate of cooked noodles, exactly one fork, and a knife is displayed."], "negative_caption": ["A plate of cooked noodles, a number of forks, and a knife is displayed."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:561807", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000183716.jpg", "positive_caption": ["A single couple of little girls sitting next to each other."], "negative_caption": ["A number of couples of little girls sitting next to each other."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:741000", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000439180.jpg", "positive_caption": ["People are riding their horses in a single parade."], "negative_caption": ["People are riding their horses in a number of parades."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:224059", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000439426.jpg", "positive_caption": ["A single person is holding a doughnut that has a bite taken out of it."], "negative_caption": ["A number of people are holding a doughnut that has a bite taken out of it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:255669", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000347335.jpg", "positive_caption": ["A plate of food with a single meat, eggs and potatoes."], "negative_caption": ["A plate of food with a number of meats, eggs and potatoes."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:517762", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000164885.jpg", "positive_caption": ["Exactly one skier flies over a mogul on the slope."], "negative_caption": ["A number of skiers fly over a mogul on the slope."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:234628", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000236721.jpg", "positive_caption": ["The meal is ready on a single tray to be eaten."], "negative_caption": ["The meal is ready on a number of trays to be eaten."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:650804", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000100624.jpg", "positive_caption": ["A girl is standing by exactly one storefront while talking on her phone."], "negative_caption": ["A girl is standing by a number of storefronts while talking on her phone."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:231040", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000141328.jpg", "positive_caption": ["A single bowl is full of pasta and vegetables."], "negative_caption": ["A number of bowls are full of pasta and vegetables."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:491438", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000478862.jpg", "positive_caption": ["Groups of people walk around a single huge, multi engine airplane."], "negative_caption": ["Groups of people walk around a number of huge, multi engine airplanes."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:116867", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000519491.jpg", "positive_caption": ["A large clock tower with exactly one statue on the top."], "negative_caption": ["A large clock tower with a number of statues on the top."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:45581", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000082688.jpg", "positive_caption": ["Two elderly people are playing exactly one interactive video game."], "negative_caption": ["Two elderly people are playing a number of interactive video games."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:611342", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000290619.jpg", "positive_caption": ["A banana is sitting beside a single large bowl storage container."], "negative_caption": ["A banana is sitting beside a number of large bowl storage containers."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:266228", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000132587.jpg", "positive_caption": ["A person sits on exactly one bench with a water bottle next to him"], "negative_caption": ["A person sits on some benches with a water bottle next to him"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:619019", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000041488.jpg", "positive_caption": ["Exactly one green and white overhead street sign on interstate 278 for queens and bronx, showing a truck restriction."], "negative_caption": ["A number of green and white overhead street signs on interstate 278 for queens and bronx, showing a truck restriction."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:138952", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000506707.jpg", "positive_caption": ["A man in a white shirt and gray pants walks toward exactly one grassy area as kids in baseball uniforms and an umpire are near him."], "negative_caption": ["A man in a white shirt and gray pants walks toward some grassy areas as kids in baseball uniforms and an umpire are near him."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:116758", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000088265.jpg", "positive_caption": ["A big brown horse pulling a single cart near a tree."], "negative_caption": ["A big brown horse pulling some carts near a tree."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:380793", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000405205.jpg", "positive_caption": ["A bus parked between two trucks in exactly one parking lot."], "negative_caption": ["A bus parked between two trucks in a number of parking lots."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:247052", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000007816.jpg", "positive_caption": ["Exactly one rider dressed in white riding a matching white motorcycle"], "negative_caption": ["Some riders dressed in white riding a matching white motorcycle"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:566030", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000265518.jpg", "positive_caption": ["A plate with food on it, exactly one fork and some kind of drink."], "negative_caption": ["A plate with food on it, a number of forks and some kind of drink."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:634783", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000042070.jpg", "positive_caption": ["A single blue, white, and green passenger bus parked at a stop."], "negative_caption": ["A number of blue, white, and green passenger buses parked at a stop."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:422240", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000311081.jpg", "positive_caption": ["The shower curtain is centered in a single middle of the tub."], "negative_caption": ["The shower curtain is centered in some middles of the tub."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:392412", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000070254.jpg", "positive_caption": ["Passengers wait at a single platform as a passenger train approaches."], "negative_caption": ["Passengers wait at some platforms as a passenger train approaches."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:234508", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000399462.jpg", "positive_caption": ["A single little girl laughs and runs with a kite in a grassy park."], "negative_caption": ["A number of little girls laugh and runs with a kite in a grassy park."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:541613", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000150224.jpg", "positive_caption": ["People lay on blankets and sit in chairs on a single beach under an umbrella."], "negative_caption": ["People lay on blankets and sit in chairs on a number of beaches under an umbrella."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:713665", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000323895.jpg", "positive_caption": ["A man is in action on exactly one green tennis court."], "negative_caption": ["A man is in action on a number of green tennis courts."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:226705", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000350405.jpg", "positive_caption": ["A man riding a snowboard down a single ski slope."], "negative_caption": ["A man riding a snowboard down some ski slopes."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:428763", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000257169.jpg", "positive_caption": ["A person is holding up exactly one hair dryer in the bathroom."], "negative_caption": ["A person is holding up a number of hair dryers in the bathroom."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:753021", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000526103.jpg", "positive_caption": ["A small elephant walks up to the fence in exactly one zoo."], "negative_caption": ["A small elephant walks up to the fence in some zoos."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:599736", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000055950.jpg", "positive_caption": ["A man is on a court with exactly one tennis racket"], "negative_caption": ["A man is on a court with a number of tennis rackets"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:799880", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000235784.jpg", "positive_caption": ["A single kid stands in the snow on his skiis"], "negative_caption": ["Some kids stand in the snow on their skiiss"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:788761", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000471023.jpg", "positive_caption": ["Exactly one vehicle is flying past a group of people"], "negative_caption": ["A number of vehicles are flying past a group of people"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:646146", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000512836.jpg", "positive_caption": ["Exactly one woman is walking her dogs   on the city sidewalks through the newly fallen snow."], "negative_caption": ["A number of women are walking their dogs on the city sidewalks through the newly fallen snow."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:15052", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000354307.jpg", "positive_caption": ["A single man has cuts in head as he lays across a bed."], "negative_caption": ["A number of men have cuts in head as they lay across a bed."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:707053", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000097679.jpg", "positive_caption": ["A couple of cars parked in exactly one lot."], "negative_caption": ["A couple of cars parked in a number of lots."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:687072", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000255917.jpg", "positive_caption": ["Many cars are waiting in traffic at a single stop light."], "negative_caption": ["Many cars are waiting in traffic at a number of stop lights."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:192106", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000515077.jpg", "positive_caption": ["A single woman is walking towards a screen that is playing a movie."], "negative_caption": ["Some women are walking towards a screen that is playing a movie."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:406623", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000368212.jpg", "positive_caption": ["A single toddler sits on a toilet while brushing his teeth."], "negative_caption": ["A number of toddlers sit on a toilet while brushing their teeth."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:15971", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000262487.jpg", "positive_caption": ["A hitter, catcher, and exactly one umpire near home plate during a baseball game."], "negative_caption": ["A hitter, catcher, and a number of umpires near home plate during a baseball game."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:283609", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000490470.jpg", "positive_caption": ["Several sailboats sit in the water in exactly one front of some trees."], "negative_caption": ["Several sailboats sit in the water in some fronts of some trees."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:717355", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000007386.jpg", "positive_caption": ["A motorcycle parked in a single front of an open garage."], "negative_caption": ["A motorcycle parked in a number of fronts of an open garage."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:530552", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000402615.jpg", "positive_caption": ["A woman holding a tennis racquet on exactly one tennis court."], "negative_caption": ["A woman holding a tennis racquet on some tennis courts."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:123887", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000102356.jpg", "positive_caption": ["Exactly one woman sits on a motorcycle with a sidecar."], "negative_caption": ["A number of women sit on a motorcycle with a sidecar."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:644500", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000505169.jpg", "positive_caption": ["A bathroom with a single toilet, tiled walls and a chained shower."], "negative_caption": ["A bathroom with some toilets, tiled walls and a chained shower."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:468174", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000114907.jpg", "positive_caption": ["A woman standing in front of a cow explaining exactly one milking machine to a group of people."], "negative_caption": ["A woman standing in front of a cow explaining some milking machines to a group of people."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:721472", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000381360.jpg", "positive_caption": ["Exactly one young surf boarder is taking a small wave."], "negative_caption": ["A number of young surf boarders are taking a small wave."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:228944", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000515350.jpg", "positive_caption": ["Exactly one surfer kneels as he catches a large wave."], "negative_caption": ["A number of surfers kneel as they catch a large wave."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:391852", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000210855.jpg", "positive_caption": ["A single fancy mirror and vanity counter top enhance this bathroom."], "negative_caption": ["Some fancy mirrors and vanity counter top enhance this bathroom."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:610398", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000268831.jpg", "positive_caption": ["A very nice looking rest room with exactly one big sink."], "negative_caption": ["A very nice looking rest room with some big sinks."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:558373", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000516173.jpg", "positive_caption": ["A woman in a wet suit carrying a surfboard into a single ocean."], "negative_caption": ["A woman in a wet suit carrying a surfboard into some oceans."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:124255", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000383443.jpg", "positive_caption": ["A large white bathroom with two vanity sinks and exactly one bathtub."], "negative_caption": ["A large white bathroom with two vanity sinks and a number of bathtubs."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:251941", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000055167.jpg", "positive_caption": ["A yellow and blue bus drives down exactly one road."], "negative_caption": ["A yellow and blue bus drives down a number of roads."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:181936", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000566758.jpg", "positive_caption": ["A bus parked by a curb on a single street"], "negative_caption": ["A bus parked by a curb on some streets"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:601379", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000108503.jpg", "positive_caption": ["Two surfers in wetsuits carrying surfboards along exactly one beach."], "negative_caption": ["Two surfers in wetsuits carrying surfboards along some beaches."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:352643", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000177015.jpg", "positive_caption": ["An apple user and his faithful cat surf exactly one web."], "negative_caption": ["An apple user and his faithful cat surf a number of webs."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:26400", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000016451.jpg", "positive_caption": ["A sandy beach with surf boards sitting on a single top of it"], "negative_caption": ["A sandy beach with surf boards sitting on some tops of it"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:783157", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000328601.jpg", "positive_caption": ["A tennis player gets ready to hit exactly one ball."], "negative_caption": ["A tennis player gets ready to hit a number of balls."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:443618", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000050006.jpg", "positive_caption": ["Boats are docked in a lake by a single road."], "negative_caption": ["Boats are docked in a lake by a number of roads."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:349529", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000056344.jpg", "positive_caption": ["A couple of monitors are on exactly one desk"], "negative_caption": ["A couple of monitors are on some desks"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:622852", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000414385.jpg", "positive_caption": ["A man walking down exactly one street next to a road filled with cars."], "negative_caption": ["A man walking down some streets next to a road filled with cars."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:222444", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000225946.jpg", "positive_caption": ["A freight train with a single green engine coming down the tracks."], "negative_caption": ["A freight train with a number of green engines coming down the tracks."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:50413", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000352491.jpg", "positive_caption": ["A very long train parked in front of a single train station."], "negative_caption": ["A very long train parked in front of some train stations."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:589433", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000317999.jpg", "positive_caption": ["A child in bed with a pacifier looks at a picture book while exactly one adult looks on"], "negative_caption": ["A child in bed with a pacifier looks at a picture book while some adults look on"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:15540", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000029640.jpg", "positive_caption": ["Exactly one recipe consisting of ham broccoli and carrots"], "negative_caption": ["A number of recipes consisting of ham broccoli and carrots"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:564972", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000098839.jpg", "positive_caption": ["A little cat is sitting on the table and watching a single tv."], "negative_caption": ["A little cat is sitting on the table and watching a number of tvs."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:436867", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000463037.jpg", "positive_caption": ["Exactly one small passenger airplane sits in the grass at the airport."], "negative_caption": ["Some small passenger airplanes sit in the grass at the airport."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:407824", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000308631.jpg", "positive_caption": ["A group of people gathered around exactly one old dirty vintage motorcycle"], "negative_caption": ["A group of people gathered around a number of old dirty vintage motorcycles"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:80049", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000284762.jpg", "positive_caption": ["A traffic light near a single street sign is red."], "negative_caption": ["A traffic light near some street signs is red."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:205161", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000031322.jpg", "positive_caption": ["A flock of swans swims in exactly one bay."], "negative_caption": ["A flock of swans swims in some bays."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:41217", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000447342.jpg", "positive_caption": ["Several vehicles providing ground transportation are shown in the photo : a single streetcar, tourbus, classic car and family cars"], "negative_caption": ["Several vehicles providing ground transportation are shown in the photo : a number of streetcars, tourbus, classic car and family cars"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:813994", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000032285.jpg", "positive_caption": ["You can see into exactly one part of a bathroom with the linen closet on the outside."], "negative_caption": ["You can see into some parts of a bathroom with the linen closet on the outside."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:733653", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000482585.jpg", "positive_caption": ["Exactly one couple of trains are on the tracks"], "negative_caption": ["A number of couples of trains are on the tracks"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:644859", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000219578.jpg", "positive_caption": ["A dog and cat are sleeping together on a single orange couch."], "negative_caption": ["A dog and cat are sleeping together on a number of orange couches."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:158211", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000248112.jpg", "positive_caption": ["A single man is swinging the tennis racket in the air."], "negative_caption": ["Some men are swinging the tennis racket in the air."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:390301", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000283037.jpg", "positive_caption": ["A single car is waiting at a red stop light at night."], "negative_caption": ["Some cars are waiting at a red stop light at night."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:36269", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000299609.jpg", "positive_caption": ["A horse is grazing in a single grassy field with a view of mountains."], "negative_caption": ["A horse is grazing in a number of grassy fields with a view of mountains."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:485481", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000309452.jpg", "positive_caption": ["Exactly one yellow bird stands perched on a tree branch."], "negative_caption": ["A number of yellow birds stand perched on a tree branch."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:635777", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000268729.jpg", "positive_caption": ["Zebras, wildebeests, and a giraffe stand in exactly one zoo enclosure."], "negative_caption": ["Zebras, wildebeests, and a giraffe stand in some zoo enclosures."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:822241", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000552842.jpg", "positive_caption": ["Exactly one baseball player is on the pitchers mound in action."], "negative_caption": ["A number of baseball players are on the pitchers mound in action."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:72714", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000117744.jpg", "positive_caption": ["A young girl with fluffy hair holds a single tennis racket."], "negative_caption": ["A young girl with fluffy hair holds a number of tennis rackets."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:807005", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000389804.jpg", "positive_caption": ["A very simple and modern bathroom with a single white toilet."], "negative_caption": ["A very simple and modern bathroom with a number of white toilets."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:634980", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000092939.jpg", "positive_caption": ["A single happy couple is cutting a decorated cake."], "negative_caption": ["A number of happy couples are cutting a decorated cake."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:725221", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000464689.jpg", "positive_caption": ["These stairs are leading up to a single open door"], "negative_caption": ["These stairs are leading up to some open doors"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:656469", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000056545.jpg", "positive_caption": ["A single bird is sitting on the small branch of the tree."], "negative_caption": ["Some birds are sitting on the small branch of the tree."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:353215", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000152771.jpg", "positive_caption": ["A lone bicycle parked in exactly one parking lot with cars parked on a street."], "negative_caption": ["A lone bicycle parked in some parking lots with cars parked on a street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:80086", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000494869.jpg", "positive_caption": ["A woman standing at a kitchen counter with a child and a single dog is behind her."], "negative_caption": ["A woman standing at a kitchen counter with a child and a number of dogs are behind her."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:439595", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000417911.jpg", "positive_caption": ["Exactly one surfer is on his board cutting through the waves."], "negative_caption": ["A number of surfers are on their boards cutting through the waves."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:53671", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000226147.jpg", "positive_caption": ["A single woman taking a photo of her food with a cell phone."], "negative_caption": ["A number of women taking a photo of their foods with a cell phone."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:769892", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000213086.jpg", "positive_caption": ["A single man holds down an oven door as he looks into the oven"], "negative_caption": ["Some men hold down an oven door as they look into the oven"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:681785", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000511599.jpg", "positive_caption": ["Several people are standing outside exactly one large boat."], "negative_caption": ["Several people are standing outside a number of large boats."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:285024", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000255749.jpg", "positive_caption": ["A bus stopped at exactly one curb to allow people to board the bus."], "negative_caption": ["A bus stopped at some curbs to allow people to board the bus."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:403938", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000376206.jpg", "positive_caption": ["A man riding a surfboard under exactly one swell of a wave"], "negative_caption": ["A man riding a surfboard under a number of swells of a wave"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:628257", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000357060.jpg", "positive_caption": ["A sandpiper probes the sand with its beak looking for food at exactly one tideline."], "negative_caption": ["A sandpiper probes the sand with its beak looking for food at a number of tidelines."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:370718", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000507893.jpg", "positive_caption": ["A bare white bathroom with a bathtub, a single window, a sink and a toilet."], "negative_caption": ["A bare white bathroom with a bathtub, a number of windows, a sink and a toilet."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:223213", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000471450.jpg", "positive_caption": ["Three bears are walking around in a single field."], "negative_caption": ["Three bears are walking around in some fields."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:426061", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000569972.jpg", "positive_caption": ["A single man on a surf board stands in shallow water"], "negative_caption": ["Some men on a surf board stand in shallow water"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:773887", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000127270.jpg", "positive_caption": ["A tennis player is swinging at a single tennis ball."], "negative_caption": ["A tennis player is swinging at some tennis balls."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:626099", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000252701.jpg", "positive_caption": ["A single young man is on his surf board with someone in the background."], "negative_caption": ["Some young men are on their surf boards with someone in the background."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:473116", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000501523.jpg", "positive_caption": ["Exactly one black cat is sitting in a bathroom sink."], "negative_caption": ["A number of black cats are sitting in a bathroom sink."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:623275", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000172595.jpg", "positive_caption": ["A purple chair is next to a desk with a computer and a single laptop."], "negative_caption": ["A purple chair is next to a desk with a computer and a number of laptops."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:67278", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000482477.jpg", "positive_caption": ["A bird is perched on a single top of a large stick."], "negative_caption": ["A bird is perched on some tops of a large stick."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:459056", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000108253.jpg", "positive_caption": ["There are two plates of food and exactly one beer in the middle of the table"], "negative_caption": ["There are two plates of food and some beers in the middle of the table"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:468051", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000486112.jpg", "positive_caption": ["A man sprays exactly one elephant with a water hose."], "negative_caption": ["A man sprays some elephants with a water hose."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:692289", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000474881.jpg", "positive_caption": ["The mountain goats are eating the grass on a single slope."], "negative_caption": ["The mountain goats are eating the grass on a number of slopes."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:630724", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000136715.jpg", "positive_caption": ["A man on a motorbike rides down a single street."], "negative_caption": ["A man on a motorbike rides down some streets."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:442599", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000046463.jpg", "positive_caption": ["A single sandwich is ready to be eaten."], "negative_caption": ["A number of sandwiches are ready to be eaten."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:238650", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000001425.jpg", "positive_caption": ["A meal is lying on a plate on exactly one table."], "negative_caption": ["A meal is lying on a plate on a number of tables."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:774635", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000532493.jpg", "positive_caption": ["Exactly one male surfer is riding a wave on a sunny day"], "negative_caption": ["A number of male surfers are riding a wave on a sunny day"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:39088", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000492110.jpg", "positive_caption": ["A man sits in a single coffee shop working on his laptop computer."], "negative_caption": ["A man sits in some coffee shops working on his laptop computer."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:95743", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000002157.jpg", "positive_caption": ["A nicely set dining table filled with food and a single cake topped with berries."], "negative_caption": ["A nicely set dining table filled with food and some cakes topped with berries."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:310740", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000183716.jpg", "positive_caption": ["Two little girls are dressed in uniform preparing for a single day"], "negative_caption": ["Two little girls are dressed in uniform preparing for a number of days"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:589398", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000246968.jpg", "positive_caption": ["A woman standing at a kitchen counter pouring something from a single measuring cup."], "negative_caption": ["A woman standing at a kitchen counter pouring something from some measuring cups."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:692811", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000276720.jpg", "positive_caption": ["A stone building with a single blue door on it"], "negative_caption": ["A stone building with some blue doors on it"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:333176", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000261888.jpg", "positive_caption": ["A bicyclist rests on exactly one bike on an empty highway with two horses walking alone up the street"], "negative_caption": ["A bicyclist rests on a number of bikes on an empty highway with two horses walking alone up the street"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:803818", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000237316.jpg", "positive_caption": ["The tiny white bathroom has a toilet and exactly one pedestal sink."], "negative_caption": ["The tiny white bathroom has a toilet and some pedestal sinks."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:609139", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000079229.jpg", "positive_caption": ["A dog follows closely behind a man on exactly one horse."], "negative_caption": ["A dog follows closely behind a man on some horses."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:88475", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000550084.jpg", "positive_caption": ["A single road sign stands next to the road."], "negative_caption": ["Some road signs stand next to the road."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:348794", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000513041.jpg", "positive_caption": ["These people are going to have exactly one pizza and wine."], "negative_caption": ["These people are going to have some pizzas and wine."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:212955", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000118367.jpg", "positive_caption": ["Exactly one sandwich has cilantro, carrots, and other vegetables."], "negative_caption": ["Some sandwiches have cilantro, carrots, and other vegetables."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:488143", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000178982.jpg", "positive_caption": ["There are two people on motorcycles approaching exactly one tunnel"], "negative_caption": ["There are two people on motorcycles approaching some tunnels"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:696877", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000515577.jpg", "positive_caption": ["A man riding skis down exactly one snow covered slope."], "negative_caption": ["A man riding skis down a number of snow covered slopes."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:181701", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000343803.jpg", "positive_caption": ["Exactly one young man in jeans is throwing a frisbee."], "negative_caption": ["A number of young men in jeans are throwing a frisbee."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:419653", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000210708.jpg", "positive_caption": ["An elephant and a baby elephant are bathing in exactly one river"], "negative_caption": ["An elephant and a baby elephant are bathing in a number of rivers"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:307942", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000206838.jpg", "positive_caption": ["Two beautiful women riding horses in exactly one ocean in bikinis."], "negative_caption": ["Two beautiful women riding horses in some oceans in bikinis."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:153250", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000330818.jpg", "positive_caption": ["A young man is standing behind a single counter, carefully looking over an array of food preparation equipment and related items."], "negative_caption": ["A young man is standing behind some counters, carefully looking over an array of food preparation equipment and related items."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:600421", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000088485.jpg", "positive_caption": ["Exactly one young man is outside playing a game of frisbee."], "negative_caption": ["A number of young men are outside playing a game of frisbee."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:240578", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000078959.jpg", "positive_caption": ["A bunch of bananas are hanging from a single banana tree"], "negative_caption": ["A bunch of bananas are hanging from some banana trees"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:651260", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000088462.jpg", "positive_caption": ["A school bus goes down a single busy road."], "negative_caption": ["A school bus goes down some busy roads."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:65070", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000352491.jpg", "positive_caption": ["A long white train has exactly one blue pin stripe."], "negative_caption": ["A long white train has a number of blue pin stripes."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:589772", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000161609.jpg", "positive_caption": ["A dog peeks out from the backpack of a man at exactly one airport"], "negative_caption": ["A dog peeks out from the backpack of a man at a number of airports"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:244687", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000330818.jpg", "positive_caption": ["A single young man is working behind a counter."], "negative_caption": ["A number of young men are working behind a counter."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:597997", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000520707.jpg", "positive_caption": ["Several people are seen walking through exactly one airport while waiting for their bags."], "negative_caption": ["Several people are seen walking through some airports while waiting for their bags."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:493268", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000465836.jpg", "positive_caption": ["Three cross - country skiers posing for the camera on a single snowy lane"], "negative_caption": ["Three cross - country skiers posing for the camera on some snowy lanes"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:270015", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000033114.jpg", "positive_caption": ["A single airplane has just landed on a runway."], "negative_caption": ["A number of airplanes have just landed on a runway."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:461020", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000257865.jpg", "positive_caption": ["The older man is playing tennis on a single court."], "negative_caption": ["The older man is playing tennis on a number of courts."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:254684", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000006213.jpg", "positive_caption": ["The bathroom had a tub with two sinks and exactly one separate shower."], "negative_caption": ["The bathroom had a tub with two sinks and some separate showers."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:827023", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000512248.jpg", "positive_caption": ["A clock is shown on the side of a single sign."], "negative_caption": ["A clock is shown on the side of some signs."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:440079", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000476119.jpg", "positive_caption": ["A man riding a skateboard down a single street in front of a red car."], "negative_caption": ["A man riding a skateboard down some streets in front of a red car."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:548557", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000378116.jpg", "positive_caption": ["A surfer wearing a single wetsuit is riding a wave."], "negative_caption": ["A surfer wearing some wetsuits is riding a wave."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:466173", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000520871.jpg", "positive_caption": ["There is exactly one large pizza pie on a white plate"], "negative_caption": ["There are some large pizza pies on a white plate"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:706087", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000429281.jpg", "positive_caption": ["A single big bin filled with some ripe yellow bananas."], "negative_caption": ["A number of big bins filled with some ripe yellow bananas."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:571400", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000197528.jpg", "positive_caption": ["Exactly one cat perched on top of a window ledge looking outside"], "negative_caption": ["A number of cats perched on top of a window ledge looking outside"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:68552", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000101068.jpg", "positive_caption": ["Exactly one little kid is swinging at a water balloon."], "negative_caption": ["Some little kids are swinging at a water balloon."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:596130", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000270883.jpg", "positive_caption": ["Exactly one woman in lingerie is laying on a soft bed."], "negative_caption": ["Some women in lingerie are laying on a soft bed."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:730209", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000364587.jpg", "positive_caption": ["A single orange and white train makes its way down the track."], "negative_caption": ["Some orange and white trains make their ways down the track."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:744195", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000324158.jpg", "positive_caption": ["Exactly one man is skate boarding down a path and a dog is running by his side."], "negative_caption": ["Some men are skate boarding down a path and a dog is running by their sides."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:310079", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000054931.jpg", "positive_caption": ["An attractive young woman leads exactly one grey horse through a paddock."], "negative_caption": ["An attractive young woman leads some grey horses through a paddock."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:19459", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000544519.jpg", "positive_caption": ["A young child brushes their teeth with exactly one blue toothbrush."], "negative_caption": ["A young child brushes their teeth with some blue toothbrushes."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:225142", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000492362.jpg", "positive_caption": ["A young man riding a single skateboard with red wheels."], "negative_caption": ["A young man riding a number of skateboards with red wheels."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:533523", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000186449.jpg", "positive_caption": ["Exactly one black and white image of an old person sitting on a bench"], "negative_caption": ["Some black and white images of an old person sitting on a bench"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:663210", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000079144.jpg", "positive_caption": ["Two bear cubs are playing on exactly one log."], "negative_caption": ["Two bear cubs are playing on some logs."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:393474", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000350388.jpg", "positive_caption": ["Exactly one white bowl of broccoli cheese soup looks delicious."], "negative_caption": ["A number of white bowls of broccoli cheese soup look delicious."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:76908", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000357081.jpg", "positive_caption": ["Two black and white cows are in exactly one grass field."], "negative_caption": ["Two black and white cows are in some grass fields."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:313054", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000135902.jpg", "positive_caption": ["A train sits running in exactly one modern station."], "negative_caption": ["A train sits running in a number of modern stations."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:802606", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000455352.jpg", "positive_caption": ["A clock is mounted to exactly one side of a tower."], "negative_caption": ["A clock is mounted to some sides of a tower."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:816232", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000227511.jpg", "positive_caption": ["There are plenty of cars parked on a single side of the street."], "negative_caption": ["There are plenty of cars parked on a number of sides of the street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:557084", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000566282.jpg", "positive_caption": ["Two men are kicking exactly one soccer ball on the city sidewalk."], "negative_caption": ["Two men are kicking a number of soccer balls on the city sidewalk."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:736709", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000476215.jpg", "positive_caption": ["A single black and white photo of a farmer standing next to horses."], "negative_caption": ["A number of black and white photos of a farmer standing next to horses."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:201915", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000465430.jpg", "positive_caption": ["Some cooked breads are on top of exactly one plate."], "negative_caption": ["Some cooked breads are on top of a number of plates."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:597920", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000263403.jpg", "positive_caption": ["A surfer flies off a single crest of a wave."], "negative_caption": ["A surfer flies off a number of crests of a wave."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:401575", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000079031.jpg", "positive_caption": ["A boy riding a wave on a single surfboard."], "negative_caption": ["A boy riding a wave on some surfboards."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:138911", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000115946.jpg", "positive_caption": ["Cars are parked on both sides of exactly one narrow street full of tall buildings."], "negative_caption": ["Cars are parked on both sides of some narrow streets full of tall buildings."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:395448", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000236412.jpg", "positive_caption": ["A single pizza pie sits in a dish on a table."], "negative_caption": ["Some pizza pies sit in a dish on a table."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:40403", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000326542.jpg", "positive_caption": ["There is exactly one male skier going down a hill"], "negative_caption": ["There are some male skiers going down a hill"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:690370", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000251824.jpg", "positive_caption": ["A person is opening exactly one plastic package with their hands."], "negative_caption": ["A person is opening some plastic packages with their hands."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:204476", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000069795.jpg", "positive_caption": ["Lavender flowers are in flower pot on a single windowsill."], "negative_caption": ["Lavender flowers are in flower pot on some windowsills."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:367080", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000381971.jpg", "positive_caption": ["Exactly one horse drawn carriage is near a fire hydrant by a curb."], "negative_caption": ["A number of horse drawn carriages are near a fire hydrant by a curb."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:517282", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000231831.jpg", "positive_caption": ["Exactly one cat stands with its paws against a desk."], "negative_caption": ["Some cats stand with their paws against a desk."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:616233", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000359781.jpg", "positive_caption": ["A single tall adult giraffe is standing next to a boulder."], "negative_caption": ["A number of tall adult giraffes are standing next to a boulder."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:687022", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000445439.jpg", "positive_caption": ["A single zebra is bent down eating some grass."], "negative_caption": ["Some zebras are bent down eating some grass."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:211465", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000516038.jpg", "positive_caption": ["A baseball player is on the mound with exactly one ball"], "negative_caption": ["A baseball player is on the mound with a number of balls"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:553985", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000225670.jpg", "positive_caption": ["A single dog is jumping in the air toward a disk"], "negative_caption": ["Some dogs are jumping in the air toward a disk"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:583363", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000445846.jpg", "positive_caption": ["A single clean kitchen with the windows white and open."], "negative_caption": ["Some clean kitchens with the windows white and open."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:13014", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000304812.jpg", "positive_caption": ["A single surfer is getting out of the water because the sun is setting."], "negative_caption": ["A number of surfers are getting out of the water because the sun is setting."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:264639", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000442456.jpg", "positive_caption": ["A single man sits on the tires of a car that rests on the ground."], "negative_caption": ["Some men sit on the tires of a car that rests on the ground."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:392181", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000425227.jpg", "positive_caption": ["Exactly one couple is on the beach on the waters edge flying a kite"], "negative_caption": ["A number of couples are on the beach on the waters edge flying a kite"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:610162", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000459634.jpg", "positive_caption": ["The motorcycle riders travel on exactly one mountain highway."], "negative_caption": ["The motorcycle riders travel on some mountain highways."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:352670", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000260105.jpg", "positive_caption": ["Exactly one white plate topped with eggs and potatoes"], "negative_caption": ["A number of white plates topped with eggs and potatoes"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:146696", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000072795.jpg", "positive_caption": ["A baseball player is at bat as a single crowd watches."], "negative_caption": ["A baseball player is at bat as a number of crowds watch."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:638515", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000230362.jpg", "positive_caption": ["A dark cloud looms behind boats docked in a single harbor."], "negative_caption": ["A dark cloud looms behind boats docked in a number of harbors."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:623744", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000553731.jpg", "positive_caption": ["Exactly one man dressed up as a clown is holding a cellphone to his ear."], "negative_caption": ["Some men dressed up as a clown are holding a cellphone to his ear."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:770075", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000431896.jpg", "positive_caption": ["Exactly one passanger train stopped on the railroad tracks."], "negative_caption": ["Some passanger trains stopped on the railroad tracks."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:614013", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000237118.jpg", "positive_caption": ["Exactly one man is taking a picture of himself"], "negative_caption": ["A number of men are taking a picture of themselves"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:528853", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000080022.jpg", "positive_caption": ["A man holding a tennis racquet on a single tennis court."], "negative_caption": ["A man holding a tennis racquet on some tennis courts."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:221226", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000444879.jpg", "positive_caption": ["Exactly one commuter train traveling down snow covered train tracks."], "negative_caption": ["Some commuter trains traveling down snow covered train tracks."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:51030", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000568981.jpg", "positive_caption": ["A man taking pictures of kids at a single skate park."], "negative_caption": ["A man taking pictures of kids at a number of skate parks."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:786985", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000263966.jpg", "positive_caption": ["A large grey horse is behind exactly one wooden fence."], "negative_caption": ["A large grey horse is behind a number of wooden fences."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:100774", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000018737.jpg", "positive_caption": ["A motorcycle parked on exactly one road in a desert"], "negative_caption": ["A motorcycle parked on some roads in a desert"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:187963", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000528578.jpg", "positive_caption": ["A castle is shown on the water next to exactly one bridge."], "negative_caption": ["A castle is shown on the water next to some bridges."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:241122", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000057149.jpg", "positive_caption": ["Automobiles stopped at an intersection because of a single passing train."], "negative_caption": ["Automobiles stopped at an intersection because of a number of passing trains."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:81115", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000499622.jpg", "positive_caption": ["A police officer riding exactly one bike in the street."], "negative_caption": ["A police officer riding a number of bikes in the street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:723641", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000479732.jpg", "positive_caption": ["A sandwich of meat, carrots, cilantro and exactly one cucumber."], "negative_caption": ["A sandwich of meat, carrots, cilantro and some cucumbers."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:123688", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000266082.jpg", "positive_caption": ["A fire hydrant waits in front of a single tall building."], "negative_caption": ["A fire hydrant waits in front of a number of tall buildings."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:97379", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000161861.jpg", "positive_caption": ["A female tennis player is posed and ready for a single ball to come."], "negative_caption": ["A female tennis player is posed and ready for a number of balls to come."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:475447", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000320554.jpg", "positive_caption": ["A cat sits under a single park bench outside."], "negative_caption": ["A cat sits under a number of park benches outside."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:664751", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000055150.jpg", "positive_caption": ["Two children sit atop a single parent's luggage in the parking lot."], "negative_caption": ["Two children sit atop a number of parent's luggages in the parking lot."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:325782", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000310862.jpg", "positive_caption": ["A man wearing a gray vest and a single red stripe tie."], "negative_caption": ["A man wearing a gray vest and a number of red stripe ties."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:768210", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000295138.jpg", "positive_caption": ["A single young man is doing tricks on his skateboard"], "negative_caption": ["Some young men are doing tricks on their skateboards"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:264596", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000402519.jpg", "positive_caption": ["A bright colored bird is sitting on a branch of exactly one full tree"], "negative_caption": ["A bright colored bird is sitting on a branch of some full trees"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:539067", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000151657.jpg", "positive_caption": ["A single couple is posing together dressed in outlandish attire"], "negative_caption": ["A number of couples are posing together dressed in outlandish attire"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:320718", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000006471.jpg", "positive_caption": ["Exactly one baseball player holds his bat and waits for the pitch."], "negative_caption": ["Some baseball players hold their bats and waits for the pitch."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:827020", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000255401.jpg", "positive_caption": ["A bathroom filled with toilets and a single tub next to a sink."], "negative_caption": ["A bathroom filled with toilets and some tubs next to a sink."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:268504", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000152465.jpg", "positive_caption": ["A rusted red fire hydrant encircled by a single old tire stands in the bare earth beside a chain link fence."], "negative_caption": ["A rusted red fire hydrant encircled by some old tires stands in the bare earth beside a chain link fence."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:775604", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000239274.jpg", "positive_caption": ["A pontoon boat ferry full of passengers pushes off from a single shore."], "negative_caption": ["A pontoon boat ferry full of passengers pushes off from some shores."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:445772", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000198928.jpg", "positive_caption": ["A woman stands next to a lamp post with exactly one street light on it."], "negative_caption": ["A woman stands next to a lamp post with a number of street lights on it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:130663", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000297085.jpg", "positive_caption": ["Exactly one cat sits directly in front of the television."], "negative_caption": ["Some cats sit directly in front of the television."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:575051", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000455937.jpg", "positive_caption": ["A man sits on a single chair and plays video games."], "negative_caption": ["A man sits on some chairs and plays video games."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:167724", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000281759.jpg", "positive_caption": ["A single row of girls holding umbrellas pose for a picture."], "negative_caption": ["A number of rows of girls holding umbrellas pose for a picture."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:291200", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000037751.jpg", "positive_caption": ["A person riding exactly one motorcycle with mountains in the background"], "negative_caption": ["A person riding a number of motorcycles with mountains in the background"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:314888", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000434479.jpg", "positive_caption": ["There is pizza on the plate on exactly one table"], "negative_caption": ["There is pizza on the plate on a number of tables"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:495617", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000265816.jpg", "positive_caption": ["A man in a horse drawn carriage parked in exactly one front of a stone building."], "negative_caption": ["A man in a horse drawn carriage parked in some fronts of a stone building."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:251189", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000297022.jpg", "positive_caption": ["A black and white photo shows men in exactly one field with a truck."], "negative_caption": ["A black and white photo shows men in a number of fields with a truck."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:529542", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000248400.jpg", "positive_caption": ["A man opens a single pizza box and stares at the camera."], "negative_caption": ["A man opens some pizza boxes and stares at the camera."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:596266", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000024610.jpg", "positive_caption": ["A small living space with a couch, desk, exactly one chair, and bookcase."], "negative_caption": ["A small living space with a couch, desk, a number of chairs, and bookcase."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:168364", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000033109.jpg", "positive_caption": ["A large semi - trailer truck driving through a single town area"], "negative_caption": ["A large semi - trailer truck driving through a number of town areas"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:213433", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000050638.jpg", "positive_caption": ["A boy carries a stuffed animal as he walks beside some flowers."], "negative_caption": ["A boy carries a stuffed animal as he walks beside a single flower."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:257703", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000142971.jpg", "positive_caption": ["A man and three children are on some surfboards"], "negative_caption": ["A man and three children are on a single surfboard"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:738292", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000418696.jpg", "positive_caption": ["A number of bright lights are shining on the street."], "negative_caption": ["A single bright light is shining on the street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:804293", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000555705.jpg", "positive_caption": ["Some cats are sitting on a pair of shoes outdoors."], "negative_caption": ["Exactly one cat is sitting on a pair of shoes outdoors."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:242296", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000013923.jpg", "positive_caption": ["Some red chairs are sitting around a small table"], "negative_caption": ["A single red chair is sitting around a small table"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:701677", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000232489.jpg", "positive_caption": ["There are some slices of pizza on a paper plate."], "negative_caption": ["There is a single slice of pizza on a paper plate."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:489329", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000159112.jpg", "positive_caption": ["Two lemon slices garnish a food topping of a number of tomatoes and diced meat mixed with a white sauce and spread over crusty bread."], "negative_caption": ["Two lemon slices garnish a food topping of a single tomato and diced meat mixed with a white sauce and spread over crusty bread."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:337846", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000104603.jpg", "positive_caption": ["A black bear is walking on a open field next to a number of trees."], "negative_caption": ["A black bear is walking on a open field next to exactly one tree."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:675637", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000402783.jpg", "positive_caption": ["Some slices of orange peels on a white plate."], "negative_caption": ["A single slice of orange peels on a white plate."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:133797", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000570834.jpg", "positive_caption": ["A white and silver subway train filled with a number of bicycles"], "negative_caption": ["A white and silver subway train filled with a single bicycle"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:469194", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000193245.jpg", "positive_caption": ["A field beside a lake is occupied by a number of kite flyers."], "negative_caption": ["A field beside a lake is occupied by exactly one kite flyer."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:228679", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000314914.jpg", "positive_caption": ["Some signs describe which rules will be enforced."], "negative_caption": ["A single sign describes which rules will be enforced."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:695693", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000201025.jpg", "positive_caption": ["Some elephants are walking through trees side by side."], "negative_caption": ["A single elephant is walking through trees side by side."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:400903", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000273711.jpg", "positive_caption": ["Some containers of food are on the table."], "negative_caption": ["A single container of food is on the table."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:279064", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000147498.jpg", "positive_caption": ["A number of birds fly around, above an empty beach"], "negative_caption": ["A single bird flies around, above an empty beach"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:244511", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000195918.jpg", "positive_caption": ["The desk has a number of monitors and one laptop on it."], "negative_caption": ["The desk has exactly one monitor and one laptop on it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:602930", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000542127.jpg", "positive_caption": ["A number of people perform flips on skis in front of a crowd."], "negative_caption": ["Exactly one person performs flips on skis in front of a crowd."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:742771", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000090891.jpg", "positive_caption": ["Some people sit in a room filled with bananas."], "negative_caption": ["A single person sits in a room filled with bananas."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:645987", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000025393.jpg", "positive_caption": ["Two men wearing some ties cross the street at night."], "negative_caption": ["Two men wearing a single tie cross the street at night."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:806280", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000060899.jpg", "positive_caption": ["A little boy has a hairbrush in a number of hands."], "negative_caption": ["A little boy has a hairbrush in exactly one hand."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:276546", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000098633.jpg", "positive_caption": ["The cake is topped with a number of whole strawberries."], "negative_caption": ["The cake is topped with exactly one whole strawberry."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:313029", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000163057.jpg", "positive_caption": ["Some people fly kites in a large park in the middle of a city."], "negative_caption": ["A single person flies kites in a large park in the middle of a city."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:240412", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000300276.jpg", "positive_caption": ["Two women are selling a number of cakes and other items inside of an outdoor stand."], "negative_caption": ["Two women are selling exactly one cake and other items inside of an outdoor stand."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:512174", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000104572.jpg", "positive_caption": ["There is an empty tiled bathroom, with some sinks and two mirrors."], "negative_caption": ["There is an empty tiled bathroom, with exactly one sink and two mirrors."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:453676", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000463842.jpg", "positive_caption": ["A single bed sits on a wood floor surrounded by a number of partially - filled bottles of colored liquid."], "negative_caption": ["A single bed sits on a wood floor surrounded by exactly one partially - filled bottle of colored liquid."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:501573", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000044195.jpg", "positive_caption": ["Some people are standing in the snow with a snow board."], "negative_caption": ["A single person is standing in the snow with a snow board."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:658161", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000452321.jpg", "positive_caption": ["A bus parked in front of a number of other buses."], "negative_caption": ["A bus parked in front of a single other bus."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:434639", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000553221.jpg", "positive_caption": ["A man is suspended from some cables and has skis on his feet."], "negative_caption": ["A man is suspended from a single cable and has skis on his feet."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:252897", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000480021.jpg", "positive_caption": ["A painting of men riding on some motorcycles next to a gas station."], "negative_caption": ["A painting of men riding on exactly one motorcycle next to a gas station."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:315002", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000177065.jpg", "positive_caption": ["Some children are learning how to play tennis."], "negative_caption": ["Exactly one child is learning how to play tennis."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:620757", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000459195.jpg", "positive_caption": ["Some young adults rest while playing frisbee golf."], "negative_caption": ["A single young adult rests while playing frisbee golf."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:480046", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000096427.jpg", "positive_caption": ["A number of young boys play tennis inside a gym"], "negative_caption": ["A single young boy plays tennis inside a gym"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:293597", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000008844.jpg", "positive_caption": ["A middle aged black woman is standing behind a table full of a number of bananas."], "negative_caption": ["A middle aged black woman is standing behind a table full of a single banana."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:406853", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000211069.jpg", "positive_caption": ["Some giraffes are walking around near some bushes."], "negative_caption": ["Some giraffes are walking around near a single bush."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:493182", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000469246.jpg", "positive_caption": ["A commuter train stops at a train station for some passengers."], "negative_caption": ["A commuter train stops at a train station for exactly one passenger."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:5746", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000186873.jpg", "positive_caption": ["A thick evergreen forest marks the boundary of a dark expanse of water, on which rests a long boat with packages at the rear and a number of people to the fore, several holding long oars."], "negative_caption": ["A thick evergreen forest marks the boundary of a dark expanse of water, on which rests a long boat with packages at the rear and exactly one person to the fore, several holding long oars."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:779382", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000079188.jpg", "positive_caption": ["Some giraffes are standing in the tall grass."], "negative_caption": ["Exactly one giraffe is standing in the tall grass."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:286427", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000375763.jpg", "positive_caption": ["A flock of sheep is crossing a grassy field with a number of trees behind them."], "negative_caption": ["A flock of sheep is crossing a grassy field with a single tree behind them."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:500294", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000507042.jpg", "positive_caption": ["Some giraffes stand near the fence of their enclosure."], "negative_caption": ["Exactly one giraffe stands near the fence of its enclosure."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:691480", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000309467.jpg", "positive_caption": ["Some people cross country skiing on a snow covered hill."], "negative_caption": ["Exactly one person crosses country skiing on a snow covered hill."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:758874", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000422706.jpg", "positive_caption": ["A number of people are leaning over a railing on a boat"], "negative_caption": ["A single person is leaning over a railing on a boat"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:425830", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000560256.jpg", "positive_caption": ["Assorted vegetables are displayed at a fruit stand including a number of bananas, oranges, apples, and cherries."], "negative_caption": ["Assorted vegetables are displayed at a fruit stand including exactly one banana, oranges, apples, and cherries."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:373385", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000511999.jpg", "positive_caption": ["Two men in some orange vests are next to a train."], "negative_caption": ["Two men in exactly one orange vest are next to a train."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:828850", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000187513.jpg", "positive_caption": ["A bathroom with a number of green walls and a toilet and a shower."], "negative_caption": ["A bathroom with a single green wall and a toilet and a shower."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:28968", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000373353.jpg", "positive_caption": ["People are crossing the street in a number of directions."], "negative_caption": ["People are crossing the street in exactly one direction."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:485819", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000505573.jpg", "positive_caption": ["A dog sits on a step perking a number of ears up"], "negative_caption": ["A dog sits on a step perking exactly one ear up"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:738242", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000392933.jpg", "positive_caption": ["A giraffe is standing on a pile of logs in a grassy field next to a number of trees."], "negative_caption": ["A giraffe is standing on a pile of logs in a grassy field next to exactly one tree."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:84456", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000226903.jpg", "positive_caption": ["A variety of desserts are being displayed for a number of people to enjoy."], "negative_caption": ["A variety of desserts are being displayed for a single person to enjoy."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:441684", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000480021.jpg", "positive_caption": ["A vintage, colored drawing of people on a number of motorcycles pulled into a gas station."], "negative_caption": ["A vintage, colored drawing of people on a single motorcycle pulled into a gas station."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:315428", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000537270.jpg", "positive_caption": ["A number of people at a desk are looking at their phones."], "negative_caption": ["A single person at a desk is looking at its phone."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:562349", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000516601.jpg", "positive_caption": ["Some snow skiers are on top of a mountain."], "negative_caption": ["A single snow skier is on top of a mountain."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:620633", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000396338.jpg", "positive_caption": ["A number of men are walking near passing trucks and cars."], "negative_caption": ["Exactly one man is walking near passing trucks and cars."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:466162", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000552371.jpg", "positive_caption": ["Two horses stand outside in their corral, with some mountains in the background."], "negative_caption": ["Two horses stand outside in their corral, with a single mountain in the background."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:327352", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000340015.jpg", "positive_caption": ["A pizza with ingredients that include tomatoes and a number of meatballs."], "negative_caption": ["A pizza with ingredients that include tomatoes and exactly one meatball."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:362002", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000142790.jpg", "positive_caption": ["A ski is laying loose while some people struggle to get up."], "negative_caption": ["A ski is laying loose while a single person struggles to get up."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:156314", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000156076.jpg", "positive_caption": ["The men are enjoying some very large pizzas."], "negative_caption": ["The men are enjoying a single very large pizza."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:696304", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000209222.jpg", "positive_caption": ["Some people are sitting on the benches and relaxing."], "negative_caption": ["A single person is sitting on the benches and relaxing."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:236724", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000182805.jpg", "positive_caption": ["A woman is playing with some dogs under an umbrella."], "negative_caption": ["A woman is playing with exactly one dog under an umbrella."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:288024", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000007281.jpg", "positive_caption": ["Two people on horseback are posing while some horses gallop on a beach shore."], "negative_caption": ["Two people on horseback are posing while a single horse gallops on a beach shore."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:156926", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000289741.jpg", "positive_caption": ["Some cruise ships docked near a beach resort"], "negative_caption": ["A single cruise ship docked near a beach resort"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:432883", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000578967.jpg", "positive_caption": ["The transit train stretches down the track under a number of power lines."], "negative_caption": ["The transit train stretches down the track under a single power line."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:53777", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000277689.jpg", "positive_caption": ["A small two tier wedding cake is embellished with some red flowers, on a table with stemware artfully arranged."], "negative_caption": ["A small two tier wedding cake is embellished with a single red flower, on a table with stemware artfully arranged."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:94588", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000298697.jpg", "positive_caption": ["Some horses are eating the hay in a large field."], "negative_caption": ["Exactly one horse is eating the hay in a large field."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:309527", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000334483.jpg", "positive_caption": ["A number of women and children are gathered around a blue cake."], "negative_caption": ["A single woman and children are gathered around a blue cake."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:430084", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000321214.jpg", "positive_caption": ["A toddler eats cake with some hands in his high chair."], "negative_caption": ["A toddler eats cake with a single hand in his high chair."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:279731", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000448410.jpg", "positive_caption": ["A train car pulls into a train station where some travelers wait nearby."], "negative_caption": ["A train car pulls into a train station where a single traveler waits nearby."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:185979", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000071711.jpg", "positive_caption": ["An indoor museum exhibit features a number of old planes."], "negative_caption": ["An indoor museum exhibit features a single old plane."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:72914", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000537827.jpg", "positive_caption": ["Some baseball players with gloves are standing in the outfield."], "negative_caption": ["A single baseball player with gloves is standing in the outfield."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:630587", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000481404.jpg", "positive_caption": ["A huge room with desks and some places to sit"], "negative_caption": ["A huge room with desks and exactly one place to sit"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:189789", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000377882.jpg", "positive_caption": ["Some boats docked on land sitting side by side next to a lake."], "negative_caption": ["A single boat docked on land sitting side by side next to a lake."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:109015", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000015517.jpg", "positive_caption": ["Some buses parked on a road outside a large bus station."], "negative_caption": ["A single bus parked on a road outside a large bus station."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:672529", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000043435.jpg", "positive_caption": ["Two surfers are riding a number of large ocean waves."], "negative_caption": ["Two surfers are riding a single large ocean wave."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:809497", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000503823.jpg", "positive_caption": ["A number of boats look like they may have been washed on shore."], "negative_caption": ["Exactly one boat looks like it may have been washed on shore."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:372321", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000165831.jpg", "positive_caption": ["Here is a large tray of a number of vegetables sitting on a counter top."], "negative_caption": ["Here is a large tray of a single vegetable sitting on a counter top."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:687786", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000322610.jpg", "positive_caption": ["People browse a number of shops while walking on a busy street."], "negative_caption": ["People browse a single shop while walking on a busy street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:38429", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000043435.jpg", "positive_caption": ["A number of people are riding on surfboards in the ocean."], "negative_caption": ["A single person is riding on surfboards in the ocean."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:797401", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000370677.jpg", "positive_caption": ["Three female workers stand in front of a number of rows of pastries."], "negative_caption": ["Three female workers stand in front of exactly one row of pastries."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:507098", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000511647.jpg", "positive_caption": ["A person is flying a kite near a number of buildings."], "negative_caption": ["A person is flying a kite near a single building."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:184847", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000017178.jpg", "positive_caption": ["Some horses stand on the street next to a silver car."], "negative_caption": ["A single horse stands on the street next to a silver car."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:624707", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000439593.jpg", "positive_caption": ["A train stopped at a train station with a number of individuals walking alongside the train."], "negative_caption": ["A train stopped at a train station with a single individual walking alongside the train."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:17338", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000531135.jpg", "positive_caption": ["A number of baseball players on the field are competing during a game."], "negative_caption": ["A single baseball player on the field is competing during a game."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:345065", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000448410.jpg", "positive_caption": ["A train is stopping to pick up some passengers on the platform."], "negative_caption": ["A train is stopping to pick up a single passenger on the platform."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:186438", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000231747.jpg", "positive_caption": ["Baseball memorabilia is displayed in some glass stacked casings."], "negative_caption": ["Baseball memorabilia is displayed in a single glass stacked casing."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:44950", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000033638.jpg", "positive_caption": ["A woman wearing some shorts bends over a frying pan on a stove."], "negative_caption": ["A woman wearing exactly one short bends over a frying pan on a stove."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:255414", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000465179.jpg", "positive_caption": ["The woman brushes a number of teeth in the bathroom."], "negative_caption": ["The woman brushes a single tooth in the bathroom."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:133728", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000364322.jpg", "positive_caption": ["Some sheep gathered in the meadow wait to be told where to go"], "negative_caption": ["A single sheep gathered in the meadow waits to be told where to go"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:526042", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000507015.jpg", "positive_caption": ["Some baseball players are on the field during a game."], "negative_caption": ["Exactly one baseball player is on the field during a game."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:397035", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000369037.jpg", "positive_caption": ["A person pets an elephant with some markings on it."], "negative_caption": ["A person pets an elephant with a single marking on it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:549516", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000474167.jpg", "positive_caption": ["A number of people are eating pizza and drinking soda at a table."], "negative_caption": ["Exactly one person is eating pizza and drinking soda at a table."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:496365", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000266981.jpg", "positive_caption": ["A number of people are walking in front of a tall building"], "negative_caption": ["Exactly one person is walking in front of a tall building"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:601732", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000012120.jpg", "positive_caption": ["A number of women play tennis on a blue court."], "negative_caption": ["Exactly one woman plays tennis on a blue court."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:582943", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000252294.jpg", "positive_caption": ["A pair of people lean out from behind a number of curtains and smile."], "negative_caption": ["A pair of people lean out from behind exactly one curtain and smile."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:740197", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000028809.jpg", "positive_caption": ["Bunches of some bananas are sitting on a shelf."], "negative_caption": ["Bunches of a single banana are sitting on a shelf."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:485863", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000567197.jpg", "positive_caption": ["A very tall building with a number of trucks parked in front of it."], "negative_caption": ["A very tall building with a single truck parked in front of it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:671705", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000156292.jpg", "positive_caption": ["A man stands in front of a wall featuring a variety of dials, some clocks, and pictures."], "negative_caption": ["A man stands in front of a wall featuring a variety of dials, a single clock, and pictures."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:141798", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000457884.jpg", "positive_caption": ["Some young boys are playing a game of baseball in the park."], "negative_caption": ["A single young boy is playing a game of baseball in the park."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:238348", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000157767.jpg", "positive_caption": ["Some people dressed in business casual clothing stand around a table of hors d'oeurves."], "negative_caption": ["Exactly one person dressed in business casual clothing stands around a table of hors d'oeurves."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:334033", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000520009.jpg", "positive_caption": ["A number of people are walking near a mini truck in a street."], "negative_caption": ["A single person is walking near a mini truck in a street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:75214", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000482978.jpg", "positive_caption": ["A train passing by with some empty seats on it."], "negative_caption": ["A train passing by with exactly one empty seat on it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:298797", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000099039.jpg", "positive_caption": ["Some plates of food and two glasses of red wine are on a table."], "negative_caption": ["Exactly one plate of food and two glasses of red wine is on a table."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:686204", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000104572.jpg", "positive_caption": ["A bathroom that features a bright tile wall and a number of big mirrors"], "negative_caption": ["A bathroom that features a bright tile wall and a single big mirror"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:823944", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000050149.jpg", "positive_caption": ["A number of bunches of bananas are hanging from a fruit stand."], "negative_caption": ["Exactly one bunch of bananas is hanging from a fruit stand."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:442271", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000111207.jpg", "positive_caption": ["Some photographs of a man in black shirt riding a skateboard."], "negative_caption": ["A single photograph of a man in black shirt riding a skateboard."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:806547", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000421757.jpg", "positive_caption": ["Some white boats travel on a wooded waterway."], "negative_caption": ["Exactly one white boat travels on a wooded waterway."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:47561", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000547886.jpg", "positive_caption": ["Four riders are on some horses on the beach."], "negative_caption": ["Four riders are on a single horse on the beach."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:259754", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000325483.jpg", "positive_caption": ["A number of men play a game with wii remotes."], "negative_caption": ["A single man plays a game with wii remotes."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:135530", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000107226.jpg", "positive_caption": ["Men race bicycles on grass pulled by a number of sleigh dogs."], "negative_caption": ["Men race bicycles on grass pulled by a single sleigh dog."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:216078", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000395180.jpg", "positive_caption": ["A person is standing with a bicycle while a number of people row by in a boat."], "negative_caption": ["A person is standing with a bicycle while exactly one person rows by in a boat."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:658865", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000114871.jpg", "positive_caption": ["There is a banana and a number of pieces of cheese on a plate."], "negative_caption": ["There is a banana and a single piece of cheese on a plate."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:141844", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000422706.jpg", "positive_caption": ["Some people watch from a large boat as a smaller boat is lowered into the ocean."], "negative_caption": ["Exactly one person watches from a large boat as a smaller boat is lowered into the ocean."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:423835", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000468501.jpg", "positive_caption": ["Some players compete in a video game as another person watches."], "negative_caption": ["A single player competes in a video game as another person watches."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:507022", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000184611.jpg", "positive_caption": ["Some people use rickshaws to transport luggage down the street."], "negative_caption": ["A single person uses rickshaws to transport luggage down the street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:89951", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000477288.jpg", "positive_caption": ["Young people dressed in costume carry some black umbrellas."], "negative_caption": ["Young people dressed in costume carry exactly one black umbrella."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:76988", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000161044.jpg", "positive_caption": ["Some airplanes are flying in the cloudy sky."], "negative_caption": ["A single airplane is flying in the cloudy sky."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:579740", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000417249.jpg", "positive_caption": ["A woman is carrying some packages in an office building"], "negative_caption": ["A woman is carrying a single package in an office building"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:750788", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000406570.jpg", "positive_caption": ["Some piles of apples, lemons, limes and oranges are available today."], "negative_caption": ["A single pile of apples, lemons, limes and oranges is available today."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:690092", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000242724.jpg", "positive_caption": ["Two very sexy women in bikinis riding some horses in the ocean."], "negative_caption": ["Two very sexy women in bikinis riding a single horse in the ocean."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:109741", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000210388.jpg", "positive_caption": ["A number of people are walking in the snow and having fun."], "negative_caption": ["Exactly one person is walking in the snow and having fun."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:478001", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000552902.jpg", "positive_caption": ["A zebra grazes in a field adjacent to a number of trees."], "negative_caption": ["A zebra grazes in a field adjacent to exactly one tree."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:697777", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000048555.jpg", "positive_caption": ["Some people race their horses down a beach."], "negative_caption": ["Exactly one person races its horse down a beach."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:378089", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000230993.jpg", "positive_caption": ["A number of women walk outside, both holding up umbrellas"], "negative_caption": ["Exactly one woman walks outside, both holding up umbrellas"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:410475", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000469192.jpg", "positive_caption": ["A car is parked on dry grass with a number of kites overhead."], "negative_caption": ["A car is parked on dry grass with exactly one kite overhead."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:21608", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000122166.jpg", "positive_caption": ["A woman on a bike rides on the street in front of a number of cars."], "negative_caption": ["A woman on a bike rides on the street in front of a single car."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:794170", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000547144.jpg", "positive_caption": ["A laptop sits on a table next to some desktop computers."], "negative_caption": ["A laptop sits on a table next to exactly one desktop computer."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:673170", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000227187.jpg", "positive_caption": ["A small black and orange bird is perched on a table with some banana peels in it."], "negative_caption": ["A small black and orange bird is perched on a table with exactly one banana peel in it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:791484", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000377670.jpg", "positive_caption": ["A group of teddy bears are dressed in a number of army outfits."], "negative_caption": ["A group of teddy bears are dressed in exactly one army outfit."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:219079", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000538458.jpg", "positive_caption": ["There are some skate boarders doing tricks on the street"], "negative_caption": ["There is a single skate boarder doing tricks on the street"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:497834", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000277051.jpg", "positive_caption": ["Some birds perched on a table near a plate of food."], "negative_caption": ["A single bird perched on a table near a plate of food."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:325666", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000384527.jpg", "positive_caption": ["The room is crowded with many things including chairs, a bicycle, and a table with a number of cups on it."], "negative_caption": ["The room is crowded with many things including chairs, a bicycle, and a table with exactly one cup on it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:319992", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000394611.jpg", "positive_caption": ["Some tall giraffes graze on bushes in an open field."], "negative_caption": ["Exactly one tall giraffe grazes on bushes in an open field."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:5720", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000049761.jpg", "positive_caption": ["Hoofed animals are outnumbered by a massive congregation of some flamingos."], "negative_caption": ["Hoofed animals are outnumbered by a massive congregation of exactly one flamingo."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:257709", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000142971.jpg", "positive_caption": ["A number of people are sitting on surfboards in the water."], "negative_caption": ["A single person is sitting on surfboards in the water."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:740716", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000517687.jpg", "positive_caption": ["Some mobile devices are lying on a table."], "negative_caption": ["Exactly one mobile device is lying on a table."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:732915", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000550349.jpg", "positive_caption": ["An orange bus is parked next to some people."], "negative_caption": ["An orange bus is parked next to exactly one person."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:454277", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000436551.jpg", "positive_caption": ["A number of black swans are floating in a lake."], "negative_caption": ["Exactly one black swan is floating in a lake."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:60205", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000173371.jpg", "positive_caption": ["There is a pizza and a number of plates on the table."], "negative_caption": ["There is a pizza and a single plate on the table."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:746237", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000493566.jpg", "positive_caption": ["This train car has a number of letters and numbers on it."], "negative_caption": ["This train car has a single letter and numbers on it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:249942", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000131386.jpg", "positive_caption": ["Some jets are flying through the air in unison."], "negative_caption": ["Exactly one jet is flying through the air in unison."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:790389", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000384666.jpg", "positive_caption": ["There are some skiers heading down a slope"], "negative_caption": ["There is exactly one skier heading down a slope"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:139869", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000233139.jpg", "positive_caption": ["A number of stone clocks are sitting on a shelf."], "negative_caption": ["Exactly one stone clock is sitting on a shelf."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:260710", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000152740.jpg", "positive_caption": ["Numerous head of a number of cattle are grazing in the grass."], "negative_caption": ["Numerous head of a single cattle are grazing in the grass."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:215792", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000284279.jpg", "positive_caption": ["A small bird contemplates how to get some seeds."], "negative_caption": ["A small bird contemplates how to get exactly one seed."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:492207", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000447522.jpg", "positive_caption": ["A dish on a blue plate contains some carrots, onions, broccoli and rice."], "negative_caption": ["A dish on a blue plate contains exactly one carrot, onions, broccoli and rice."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:421081", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000467315.jpg", "positive_caption": ["A glass vase with some flowers inside of it"], "negative_caption": ["A glass vase with exactly one flower inside of it"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:630928", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000132329.jpg", "positive_caption": ["Some bottles sit in an otherwise empty refrigerator."], "negative_caption": ["Exactly one bottle sits in an otherwise empty refrigerator."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:39561", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000561009.jpg", "positive_caption": ["A bird with some brown wings and head perched in a tree."], "negative_caption": ["A bird with exactly one brown wing and head perched in a tree."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:702610", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000287874.jpg", "positive_caption": ["A number of people are waiting beside the blue train pulling beside the platform."], "negative_caption": ["Exactly one person is waiting beside the blue train pulling beside the platform."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:734534", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000224222.jpg", "positive_caption": ["A surfer is riding a wave in the ocean with some swimmers"], "negative_caption": ["A surfer is riding a wave in the ocean with a single swimmer"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:537619", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000376310.jpg", "positive_caption": ["A rest room with a number of sinks and a well lighted mirror."], "negative_caption": ["A rest room with a single sink and a well lighted mirror."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:294274", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000087470.jpg", "positive_caption": ["A number of cows travel down the side of a street"], "negative_caption": ["Exactly one cow travels down the side of a street"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:619110", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000110884.jpg", "positive_caption": ["A small cramped bathroom slightly cluttered with a number of dingy walls."], "negative_caption": ["A small cramped bathroom slightly cluttered with a single dingy wall."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:725472", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000173799.jpg", "positive_caption": ["Some people stand in front of a bunch of elephants"], "negative_caption": ["A single person stands in front of a bunch of elephants"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:670513", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000402346.jpg", "positive_caption": ["A number of tomatoes sit in a black bowl next to a flower."], "negative_caption": ["Exactly one tomato sits in a black bowl next to a flower."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:184130", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000259597.jpg", "positive_caption": ["A young boy is recording a performance on a cellphone of some people."], "negative_caption": ["A young boy is recording a performance on a cellphone of exactly one person."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:56089", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000573626.jpg", "positive_caption": ["There are some horses standing in the rocks near the water."], "negative_caption": ["There is a single horse standing in the rocks near the water."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:204757", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000168458.jpg", "positive_caption": ["A number of flowers sit in a vase, on a table, beside a watering container."], "negative_caption": ["A single flower sits in a vase, on a table, beside a watering container."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:691996", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000383337.jpg", "positive_caption": ["There is a box filled with some glazed doughnuts"], "negative_caption": ["There is a box filled with exactly one glazed doughnut"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:139826", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000219440.jpg", "positive_caption": ["Here is a image of some zoo animals."], "negative_caption": ["Here is a image of a single zoo animal."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:615806", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000497867.jpg", "positive_caption": ["A bus full of some people drives down a city street"], "negative_caption": ["A bus full of a single person drives down a city street"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:517765", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000248284.jpg", "positive_caption": ["This person is leaving some footprints in the snow"], "negative_caption": ["This person is leaving a single footprint in the snow"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:696582", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000363840.jpg", "positive_caption": ["Some laptops, computer, keyboard and other electrical gadgets are on the table."], "negative_caption": ["A single laptop, computer, keyboard and other electrical gadgets is on the table."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:322035", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000480122.jpg", "positive_caption": ["This is a wood table with a number of bananas on it"], "negative_caption": ["This is a wood table with exactly one banana on it"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:693528", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000066817.jpg", "positive_caption": ["A meal of fried food, some beans, rice, cream and fruit."], "negative_caption": ["A meal of fried food, exactly one bean, rice, cream and fruit."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:414930", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000023781.jpg", "positive_caption": ["Various fruits and a number of vegetables are on display close together."], "negative_caption": ["Various fruits and a single vegetable are on display close together."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:298338", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000332351.jpg", "positive_caption": ["A number of surfers are catching the waves near the beach"], "negative_caption": ["A single surfer is catching the waves near the beach"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:552942", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000246454.jpg", "positive_caption": ["A black and white photo of a girl petting some dogs."], "negative_caption": ["A black and white photo of a girl petting exactly one dog."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:68597", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000572303.jpg", "positive_caption": ["A train with a number of mirrors on the outside sits on some tracks."], "negative_caption": ["A train with a single mirror on the outside sits on some tracks."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:179899", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000470924.jpg", "positive_caption": ["A group of people sit at a wooden table with a number of pizzas on it in an outdoor place."], "negative_caption": ["A group of people sit at a wooden table with a single pizza on it in an outdoor place."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:328872", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000410612.jpg", "positive_caption": ["A boat passes by some waterfront houses flanked by trees."], "negative_caption": ["A boat passes by exactly one waterfront house flanked by trees."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:24377", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000528862.jpg", "positive_caption": ["In a large area a number of giraffes stand behind a fenced area."], "negative_caption": ["In a large area a single giraffe stands behind a fenced area."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:331073", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000292908.jpg", "positive_caption": ["There is a surfer at the beach riding a number of waves in the ocean"], "negative_caption": ["There is a surfer at the beach riding exactly one wave in the ocean"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:455952", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000186873.jpg", "positive_caption": ["A group of people paddle a long canoe in a clear lake bordered by a number of pine woods."], "negative_caption": ["A group of people paddle a long canoe in a clear lake bordered by exactly one pine wood."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:769980", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000220858.jpg", "positive_caption": ["A boat is on the beach while some men dig in the sand in the distance."], "negative_caption": ["A boat is on the beach while a single man digs in the sand in the distance."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:223682", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000203931.jpg", "positive_caption": ["A professional baseball player takes a swing in front of a number of fans in a crowded stadium."], "negative_caption": ["A professional baseball player takes a swing in front of exactly one fan in a crowded stadium."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:821617", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000360325.jpg", "positive_caption": ["Crowded sheep of a number of different colors stand in an enclosure."], "negative_caption": ["Crowded sheep of exactly one different color stand in an enclosure."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:184689", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000332318.jpg", "positive_caption": ["A number of herd animals are on the grass by a mountain."], "negative_caption": ["A single herd animal is on the grass by a mountain."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:404081", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000281687.jpg", "positive_caption": ["A lady talks on a cell phone as a number of people walk by"], "negative_caption": ["A lady talks on a cell phone as exactly one person walks by"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:629716", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000090108.jpg", "positive_caption": ["A bathroom with some blue and white walls"], "negative_caption": ["A bathroom with exactly one blue and white wall"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:681137", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000002685.jpg", "positive_caption": ["A number of people line up to taste some wine."], "negative_caption": ["A single person lines up to taste some wine."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:572793", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000182441.jpg", "positive_caption": ["A man is standing outside of the water observing the huge flock of some birds."], "negative_caption": ["A man is standing outside of the water observing the huge flock of a single bird."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:817864", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000041635.jpg", "positive_caption": ["A number of cows stand in a field behind a barbed wire fence."], "negative_caption": ["A single cow stands in a field behind a barbed wire fence."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:75604", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000312192.jpg", "positive_caption": ["A pizza with a number of lots of greens and meat is sitting on the table."], "negative_caption": ["A pizza with a single lot of greens and meat is sitting on the table."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:565575", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000300659.jpg", "positive_caption": ["A number of jets fly in formation leaving trails of smoke behind them."], "negative_caption": ["Exactly one jet flies in formation leaving trails of smoke behind them."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:320904", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000433103.jpg", "positive_caption": ["Several children are seated in a row and holding a number of electronic keyboards."], "negative_caption": ["Several children are seated in a row and holding exactly one electronic keyboard."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:572423", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000430377.jpg", "positive_caption": ["A woman posing on some skis with a ski lift in the background."], "negative_caption": ["A woman posing on a single ski with a ski lift in the background."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:543261", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000030504.jpg", "positive_caption": ["A tall man is on a number of snow skis on a pathway."], "negative_caption": ["A tall man is on a single snow ski on a pathway."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:264601", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000496571.jpg", "positive_caption": ["A person is eating at a table with some plates, a fork, knife, spoon, cup, and cell phone on it."], "negative_caption": ["A person is eating at a table with a single plate, a fork, knife, spoon, cup, and cell phone on it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:273003", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000293794.jpg", "positive_caption": ["A number of bunches of bananas are piled up at a market with some shoppers looking around."], "negative_caption": ["A single bunch of bananas are piled up at a market with some shoppers looking around."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:53227", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000415990.jpg", "positive_caption": ["Some men are checking in on the herd of cows."], "negative_caption": ["A single man is checking in on the herd of cows."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:788817", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000441491.jpg", "positive_caption": ["Some women are taking a bite out of the same piece of pizza."], "negative_caption": ["A single woman is taking a bite out of the same piece of pizza."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:94857", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000429011.jpg", "positive_caption": ["A number of toy vehicles and a police box are set up in a street scene."], "negative_caption": ["Exactly one toy vehicle and a police box are set up in a street scene."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:420159", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000171298.jpg", "positive_caption": ["A number of yellow coach buses parked in a line."], "negative_caption": ["A single yellow coach bus parked in a line."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:61589", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000326174.jpg", "positive_caption": ["A group of people are taking a number of surfing lessons."], "negative_caption": ["A group of people are taking a single surfing lesson."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:52670", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000252219.jpg", "positive_caption": ["Some city dwellers walk by as a homeless man begs for cash."], "negative_caption": ["Exactly one city dweller walks by as a homeless man begs for cash."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:109132", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000211042.jpg", "positive_caption": ["A cat has some front paws on a toilet seat."], "negative_caption": ["A cat has a single front paw on a toilet seat."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:714160", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000573626.jpg", "positive_caption": ["Some horses stand on rocks near a river."], "negative_caption": ["Exactly one horse stands on rocks near a river."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:192316", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000438862.jpg", "positive_caption": ["Some teams are kicking a soccer ball."], "negative_caption": ["Exactly one team is kicking a soccer ball."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:408816", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000435081.jpg", "positive_caption": ["A collage displays colorful deserts and some fresh vegetables."], "negative_caption": ["A collage displays colorful deserts and exactly one fresh vegetable."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:92804", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000094157.jpg", "positive_caption": ["A large brick clock tower stands high above a number of trees."], "negative_caption": ["A large brick clock tower stands high above a single tree."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:196048", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000066231.jpg", "positive_caption": ["Chefs and some cooks are preparing meals in a restaurant kichen"], "negative_caption": ["Chefs and a single cook are preparing meals in a restaurant kichen"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:435280", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000117492.jpg", "positive_caption": ["A crowd of a number of adults and children are at a park."], "negative_caption": ["A crowd of a single adult and children are at a park."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:247953", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000090208.jpg", "positive_caption": ["Some green and red double decker buses lined up parked."], "negative_caption": ["Exactly one green and red double decker bus lined up parked."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:132162", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000555972.jpg", "positive_caption": ["There are some purple flowers in a wooden vase."], "negative_caption": ["There is exactly one purple flower in a wooden vase."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:410160", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000308587.jpg", "positive_caption": ["A number of people are windsurfing near a beach on a cloudy day."], "negative_caption": ["A single person is windsurfing near a beach on a cloudy day."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:823606", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000378244.jpg", "positive_caption": ["A person skis through some trees down a hill"], "negative_caption": ["A person skis through a single tree down a hill"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:425529", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000433103.jpg", "positive_caption": ["Several children sit together while playing with a number of plastic laptop computers."], "negative_caption": ["Several children sit together while playing with a single plastic laptop computer."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:574361", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000293200.jpg", "positive_caption": ["There are some people on this field flying kites"], "negative_caption": ["There is a single person on this field flying kites"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:279848", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000502732.jpg", "positive_caption": ["A large silver refrigerator with a number of doors and an ice dispenser."], "negative_caption": ["A large silver refrigerator with exactly one door and an ice dispenser."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:172479", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000459809.jpg", "positive_caption": ["A group of people fly some kites in the air."], "negative_caption": ["A group of people fly a single kite in the air."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:442575", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000335081.jpg", "positive_caption": ["Stuffed bears and a number of ducks are lined up on the floor."], "negative_caption": ["Stuffed bears and a single duck are lined up on the floor."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:279301", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000045596.jpg", "positive_caption": ["The passage between the modern buildings is used by a number of bicycle riders."], "negative_caption": ["The passage between the modern buildings is used by exactly one bicycle rider."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:516276", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000222559.jpg", "positive_caption": ["Some people walk on the beach with boats nearby."], "negative_caption": ["A single person walks on the beach with boats nearby."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:298235", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000097994.jpg", "positive_caption": ["A number of laptop computers and a desktop computer sit next to each other."], "negative_caption": ["Exactly one laptop computer and a desktop computer sit next to each other."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:140824", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000347664.jpg", "positive_caption": ["A number of cows walk along a beach with a mountain in the distance."], "negative_caption": ["Exactly one cow walks along a beach with a mountain in the distance."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:250297", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000097022.jpg", "positive_caption": ["A kitchen filled with a number of wooden cabinets and a microwave oven."], "negative_caption": ["A kitchen filled with a single wooden cabinet and a microwave oven."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:204330", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000320743.jpg", "positive_caption": ["A number of boys with wide hats are riding elephants on the dirt."], "negative_caption": ["Exactly one boy with wide hats is riding elephants on the dirt."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:383974", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000094614.jpg", "positive_caption": ["A man riding some skis down the side of a snow covered ski slope."], "negative_caption": ["A man riding a single ski down the side of a snow covered ski slope."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:121305", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000305317.jpg", "positive_caption": ["A number of people are flying kites in an open field of grass."], "negative_caption": ["A single person is flying kites in an open field of grass."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:706828", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000331569.jpg", "positive_caption": ["A fruit smoothie is on display on a plate with a number of strawberries for garnish."], "negative_caption": ["A fruit smoothie is on display on a plate with exactly one strawberry for garnish."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:445702", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000480842.jpg", "positive_caption": ["A number of giraffes are towering over the plants under them."], "negative_caption": ["Exactly one giraffe is towering over the plants under them."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:224248", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000529966.jpg", "positive_caption": ["Two bowls of some oranges are sitting on a metal surface."], "negative_caption": ["Two bowls of a single orange are sitting on a metal surface."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:666182", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000322610.jpg", "positive_caption": ["A woman holding an umbrella stands as some people walk past."], "negative_caption": ["A woman holding an umbrella stands as a single person walks past."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:40109", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000001761.jpg", "positive_caption": ["A number of planes fly over a bridge in sydney, australia, with the sydney opera house in the background."], "negative_caption": ["Exactly one plane flies over a bridge in sydney, australia, with the sydney opera house in the background."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:119546", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000451714.jpg", "positive_caption": ["A man riding some skis on top of   a snow covered hill."], "negative_caption": ["A man riding a single ski on top of a snow covered hill."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:336280", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000207728.jpg", "positive_caption": ["Some white goats in a snowy field look at a tree"], "negative_caption": ["Exactly one white goat in a snowy field looks at a tree"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:108495", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000398377.jpg", "positive_caption": ["A number of commuters their their cell phones during a train ride"], "negative_caption": ["A single commuter its their cell phone during a train ride"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:395795", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000415536.jpg", "positive_caption": ["A bus is driving on a wet road with a number of green trees on the roadside."], "negative_caption": ["A bus is driving on a wet road with a single green tree on the roadside."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:433459", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000493799.jpg", "positive_caption": ["A plate of food containing some carrots, potatoes and meat."], "negative_caption": ["A plate of food containing exactly one carrot, potatoes and meat."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:169290", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000236308.jpg", "positive_caption": ["Some people are skiing down the snow covered hill."], "negative_caption": ["Exactly one person is skiing down the snow covered hill."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:243871", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000343496.jpg", "positive_caption": ["The woman who has bought some groceries is crossing the street."], "negative_caption": ["The woman who has bought a single grocery is crossing the street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:357811", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000035682.jpg", "positive_caption": ["A meal of some donuts and a beverage is seen in front of a man at a restaurant."], "negative_caption": ["A meal of a single donut and a beverage is seen in front of a man at a restaurant."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:673764", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000366711.jpg", "positive_caption": ["A man is squeezing orange juice from a pile of some oranges."], "negative_caption": ["A man is squeezing orange juice from a pile of exactly one orange."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:455026", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000178744.jpg", "positive_caption": ["A yellow boat with a number of people is in a canal."], "negative_caption": ["A yellow boat with exactly one person is in a canal."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:441366", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000002532.jpg", "positive_caption": ["A skier stands on a number of skis at the top of a snowy plateau."], "negative_caption": ["A skier stands on a single ski at the top of a snowy plateau."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:178816", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000484893.jpg", "positive_caption": ["A number of children reach over a short barrier to pet small sheep."], "negative_caption": ["A single child reaches over a short barrier to pet small sheep."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:249434", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000314182.jpg", "positive_caption": ["Four bowls of some different eatables are kept on the slab."], "negative_caption": ["Four bowls of a single different eatable are kept on the slab."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:320589", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000153568.jpg", "positive_caption": ["A stop sign with some additional warnings taped to it."], "negative_caption": ["A stop sign with exactly one additional warning taped to it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:169084", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000038829.jpg", "positive_caption": ["Some boys riding on a single bicycle on a city street"], "negative_caption": ["A single boy riding on a single bicycle on a city street"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:432092", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000462371.jpg", "positive_caption": ["Several people are gathered at a reception with some appetizers."], "negative_caption": ["Several people are gathered at a reception with a single appetizer."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:683741", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000387916.jpg", "positive_caption": ["Some skiers stand on a flat portion of the mountain."], "negative_caption": ["Exactly one skier stands on a flat portion of the mountain."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:60786", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000302165.jpg", "positive_caption": ["A number of cows are laying in their stalls in the barn."], "negative_caption": ["A single cow is laying in its stall in the barn."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:185603", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000448410.jpg", "positive_caption": ["A train is entering its stop with a number of people waiting for it."], "negative_caption": ["A train is entering its stop with exactly one person waiting for it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:183174", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000128148.jpg", "positive_caption": ["A large living room with some leather couches and wood flooring"], "negative_caption": ["A large living room with exactly one leather couch and wood flooring"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:107034", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000438774.jpg", "positive_caption": ["A small party of some people eats some pizza on a table"], "negative_caption": ["A small party of exactly one person eats some pizza on a table"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:790659", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000183127.jpg", "positive_caption": ["A huge, crashing wave with some lots of spray is carrying a kneeling wet - suited surfer to shore."], "negative_caption": ["A huge, crashing wave with exactly one lot of spray is carrying a kneeling wet - suited surfer to shore."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:777417", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000359833.jpg", "positive_caption": ["The baby is standing next to several boxes of some apples."], "negative_caption": ["The baby is standing next to several boxes of exactly one apple."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:575353", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000199977.jpg", "positive_caption": ["A plane flies through the air with a number of fumes coming out the back"], "negative_caption": ["A plane flies through the air with a single fume coming out the back"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:362797", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000091779.jpg", "positive_caption": ["Three sausages in some buns are covered with various toppings."], "negative_caption": ["Three sausages in a single bun are covered with various toppings."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:170387", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000043435.jpg", "positive_caption": ["A number of surfers ride towering waves on the open ocean."], "negative_caption": ["Exactly one surfer rides towering waves on the open ocean."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:801142", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000034760.jpg", "positive_caption": ["Some cleaning products are on the counter of the bathroom."], "negative_caption": ["A single cleaning product is on the counter of the bathroom."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:491321", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000434247.jpg", "positive_caption": ["A couple of people are riding some horses on the beach"], "negative_caption": ["A couple of people are riding a single horse on the beach"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:435286", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000374083.jpg", "positive_caption": ["A man and little girl are in a kitchen looking at some cakes."], "negative_caption": ["A man and little girl are in a kitchen looking at a single cake."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:774004", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000575970.jpg", "positive_caption": ["A neatly arranged room with some lights."], "negative_caption": ["A neatly arranged room with a single light."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:804321", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000507235.jpg", "positive_caption": ["A table filled with some dishes of very tasty looking food."], "negative_caption": ["A table filled with exactly one dish of very tasty looking food."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:526416", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000507797.jpg", "positive_caption": ["Some elderly women debark a bus at a station."], "negative_caption": ["Exactly one elderly woman debarks a bus at a station."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:397007", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000567740.jpg", "positive_caption": ["There are a number of people standing in the snow on skis."], "negative_caption": ["There is a single person standing in the snow on skis."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:236086", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000544811.jpg", "positive_caption": ["A number of large birds are flying over the calm water."], "negative_caption": ["A single large bird is flying over the calm water."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:733786", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000556193.jpg", "positive_caption": ["A number of men are playing a wii video game."], "negative_caption": ["A single man is playing a wii video game."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:168814", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000559099.jpg", "positive_caption": ["There are some cows walking around the grass"], "negative_caption": ["There is a single cow walking around the grass"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:663714", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000300341.jpg", "positive_caption": ["The two men are playing video games while some others watch"], "negative_caption": ["The two men are playing video games while a single other watches"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:578618", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000137950.jpg", "positive_caption": ["A plane flies through the sky above some trees."], "negative_caption": ["A plane flies through the sky above exactly one tree."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:103064", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000413395.jpg", "positive_caption": ["A man sitting on a couch has some cats on his lap."], "negative_caption": ["A man sitting on a couch has a single cat on his lap."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:4116", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000305309.jpg", "positive_caption": ["Some young boys in a black and white picture are playing baseball."], "negative_caption": ["Exactly one young boy in a black and white picture is playing baseball."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:605973", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000406611.jpg", "positive_caption": ["There are a number of people ready to ski on this beautiful day."], "negative_caption": ["There is exactly one person ready to ski on this beautiful day."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:441344", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000209753.jpg", "positive_caption": ["A woman with some large black tear drop earrings and a black dress looks at her cell phone."], "negative_caption": ["A woman with exactly one large black tear drop earring and a black dress looks at her cell phone."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:437537", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000231088.jpg", "positive_caption": ["Several umbrellas of a number of different colors are hanging in the sun."], "negative_caption": ["Several umbrellas of a single different color are hanging in the sun."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:5171", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000110449.jpg", "positive_caption": ["A man is standing with some hands on a table"], "negative_caption": ["A man is standing with exactly one hand on a table"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:594315", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000418961.jpg", "positive_caption": ["A decorative clock has some roman numerals on its face."], "negative_caption": ["A decorative clock has a single roman numeral on its face."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:382425", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000015660.jpg", "positive_caption": ["A number of para - gliders can be seen in the blue sky."], "negative_caption": ["Exactly one para - glider can be seen in the blue sky."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:498292", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000547886.jpg", "positive_caption": ["A group of people are riding a number of horses on a beach."], "negative_caption": ["A group of people are riding a single horse on a beach."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:261221", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000407002.jpg", "positive_caption": ["A man wearing snow gear poses for a photo while standing on a number of skis"], "negative_caption": ["A man wearing snow gear poses for a photo while standing on exactly one ski"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:295472", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000376625.jpg", "positive_caption": ["The trolley car runs up and down the street on some train rails."], "negative_caption": ["The trolley car runs up and down the street on a single train rail."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:751654", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000256192.jpg", "positive_caption": ["A yellow motorcycle is parked on a road with some bystanders"], "negative_caption": ["A yellow motorcycle is parked on a road with exactly one bystander"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:779997", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000031050.jpg", "positive_caption": ["A vase full of a number of flowers is sitting on display."], "negative_caption": ["A vase full of exactly one flower is sitting on display."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:240159", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000318455.jpg", "positive_caption": ["Some cupcakes and half of a cake sit on a table."], "negative_caption": ["A single cupcake and half of a cake sit on a table."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:250429", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000005600.jpg", "positive_caption": ["A plate has two bowls on it with some different types of food, one looks like pickled onions and the other looks like cooked meat."], "negative_caption": ["A plate has two bowls on it with exactly one different type of food, one looks like pickled onions and the other looks like cooked meat."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:611063", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000240049.jpg", "positive_caption": ["A woman and a baby look at some giraffes at the zoo"], "negative_caption": ["A woman and a baby look at a single giraffe at the zoo"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:716918", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000002431.jpg", "positive_caption": ["A meal of burnt toast slices with a number of condiments on the side."], "negative_caption": ["A meal of burnt toast slices with exactly one condiment on the side."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:350465", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000124798.jpg", "positive_caption": ["A bus travels down the street with some cars on a sunny day"], "negative_caption": ["A bus travels down the street with exactly one car on a sunny day"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:791595", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000460683.jpg", "positive_caption": ["A man is wearing a tie with some words on it"], "negative_caption": ["A man is wearing a tie with exactly one word on it"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:122942", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000278848.jpg", "positive_caption": ["Some people are standing in the rain alongside a bus."], "negative_caption": ["Exactly one person is standing in the rain alongside a bus."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:583164", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000276804.jpg", "positive_caption": ["A number of baseball players engaged in a baseball game."], "negative_caption": ["Exactly one baseball player engaged in a baseball game."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:157945", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000574425.jpg", "positive_caption": ["A number of old fashioned buses parked on the side of the road."], "negative_caption": ["A single old fashioned bus parked on the side of the road."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:676695", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000469246.jpg", "positive_caption": ["A number of passengers wait for a train as it approaches the platform."], "negative_caption": ["Exactly one passenger waits for a train as it approaches the platform."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:6262", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000129756.jpg", "positive_caption": ["There is a man standing on a hill with sheep and some dogs"], "negative_caption": ["There is a man standing on a hill with sheep and a single dog"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:458612", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000019042.jpg", "positive_caption": ["A large bird is perched on a number of rocks in a river."], "negative_caption": ["A large bird is perched on a single rock in a river."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:539116", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000521282.jpg", "positive_caption": ["A vase filled with some yellow and white flowers."], "negative_caption": ["A vase filled with a single yellow and white flower."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:696837", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000411817.jpg", "positive_caption": ["Some people are looking at a number of different television sets"], "negative_caption": ["Some people are looking at a single different television set"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:542683", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000389315.jpg", "positive_caption": ["There is a suitcase that is full of some books"], "negative_caption": ["There is a suitcase that is full of a single book"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:148038", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000290592.jpg", "positive_caption": ["A cluster of a number of black and white sheep hang out by a fence."], "negative_caption": ["A cluster of a single black and white sheep hang out by a fence."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:612135", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000183437.jpg", "positive_caption": ["A number of women are going for a ride on an elephant"], "negative_caption": ["A single woman is going for a ride on an elephant"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:465519", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000249129.jpg", "positive_caption": ["There are a number of stuffed teddy bears sitting on chairs at a table"], "negative_caption": ["There is exactly one stuffed teddy bear sitting on chairs at a table"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:121914", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000273711.jpg", "positive_caption": ["There are some different types of food gathered on the table"], "negative_caption": ["There is exactly one different type of food gathered on the table"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:277591", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000061171.jpg", "positive_caption": ["A number of cows and a horse are eating hay."], "negative_caption": ["Exactly one cow and a horse is eating hay."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:782351", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000002685.jpg", "positive_caption": ["A couple of people are standing in front of some wine bottles"], "negative_caption": ["A couple of people are standing in front of a single wine bottle"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:577428", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000032817.jpg", "positive_caption": ["A number of men are doing work in a bathroom."], "negative_caption": ["Exactly one man is doing work in a bathroom."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:401379", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000086755.jpg", "positive_caption": ["Some snow skiers are coming down a hill"], "negative_caption": ["Exactly one snow skier is coming down a hill"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:546540", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000357903.jpg", "positive_caption": ["A pizza topped with cheese, some veggies and an egg."], "negative_caption": ["A pizza topped with cheese, exactly one veggie and an egg."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:639767", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000470924.jpg", "positive_caption": ["Some people enjoying a meal are posing for their picture."], "negative_caption": ["Exactly one person enjoying a meal is posing for its picture."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:332400", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000097924.jpg", "positive_caption": ["Some people try to guide a horse into a trailer."], "negative_caption": ["A single person tries to guide a horse into a trailer."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:827558", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000509403.jpg", "positive_caption": ["The dog runs near an adult who plays with some children."], "negative_caption": ["The dog runs near an adult who plays with a single child."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:498538", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000561958.jpg", "positive_caption": ["Some people attend the ski event dressed in warm clothing."], "negative_caption": ["Exactly one person attends the ski event dressed in warm clothing."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:133747", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000505942.jpg", "positive_caption": ["A number of people have a conversation at an intersection"], "negative_caption": ["Exactly one person has a conversation at an intersection"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:418228", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000206218.jpg", "positive_caption": ["A small tank like vehicle with some wheels and a camera attached to the top, along with a laptop computer resting on top of it."], "negative_caption": ["A small tank like vehicle with a single wheel and a camera attached to the top, along with a laptop computer resting on top of it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:595173", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000351530.jpg", "positive_caption": ["There is a long line of wooden chairs and a number of women sit."], "negative_caption": ["There is a long line of wooden chairs and a single woman sits."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:245575", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000169169.jpg", "positive_caption": ["A number of people are walking around a plaza that has a sign that reads\"  spring in the city\"  ."], "negative_caption": ["Exactly one person is walking around a plaza that has a sign that reads\" spring in the city\" ."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:595683", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000394611.jpg", "positive_caption": ["Some giraffes are grazing in a field of grass."], "negative_caption": ["Exactly one giraffe is grazing in a field of grass."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:10427", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000061268.jpg", "positive_caption": ["A train carrying some freight containers is on the tracks."], "negative_caption": ["A train carrying a single freight container is on the tracks."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:686203", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000350023.jpg", "positive_caption": ["A street that has some lanes of traffic."], "negative_caption": ["A street that has exactly one lane of traffic."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:678178", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000276024.jpg", "positive_caption": ["Some men on horses drive cattle down the road."], "negative_caption": ["A single man on horses drives cattle down the road."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:4556", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000211120.jpg", "positive_caption": ["Three stuffed animals are dressed and sitting on a blanket in front of a number of empty plates."], "negative_caption": ["Three stuffed animals are dressed and sitting on a blanket in front of exactly one empty plate."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:772286", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000060102.jpg", "positive_caption": ["A number of soccer players try to gain possession of the ball."], "negative_caption": ["A single soccer player tries to gain possession of the ball."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:175560", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000293625.jpg", "positive_caption": ["Some friends are sitting on the couch, enjoying a game played on the wii."], "negative_caption": ["Exactly one friend is sitting on the couch, enjoying a game played on the wii."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:356563", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000179898.jpg", "positive_caption": ["A child is holding a number of hot dogs up to the photographer."], "negative_caption": ["A child is holding a single hot dog up to the photographer."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:196327", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000121586.jpg", "positive_caption": ["A small tv is affixed to the wall with some shelves below it."], "negative_caption": ["A small tv is affixed to the wall with exactly one shelf below it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:742364", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000421757.jpg", "positive_caption": ["A number of boats are floating on the river near the shore."], "negative_caption": ["A single boat is floating on the river near the shore."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:42446", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000308587.jpg", "positive_caption": ["The photo shows some ways to enjoy the beach -- kite flying, bathing, lying in the sun, walking along the sand."], "negative_caption": ["The photo shows exactly one way to enjoy the beach -- kite flying, bathing, lying in the sun, walking along the sand."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:742122", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000389381.jpg", "positive_caption": ["A plastic bento box filled with rice, some vegetables and fresh fruit"], "negative_caption": ["A plastic bento box filled with rice, a single vegetable and fresh fruit"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:651488", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000098633.jpg", "positive_caption": ["A square, white cake sits on a round plate and is decorated with some strawberries."], "negative_caption": ["A square, white cake sits on a round plate and is decorated with a single strawberry."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:313116", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000008021.jpg", "positive_caption": ["A number of people watch a man delivering a lecture on a screen."], "negative_caption": ["A single person watches a man delivering a lecture on a screen."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:84338", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000523100.jpg", "positive_caption": ["A person fills a number of jars with orange slices from a large bowl."], "negative_caption": ["A person fills a single jar with orange slices from a large bowl."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:636242", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000036844.jpg", "positive_caption": ["A living room with wooden floors and some white walls."], "negative_caption": ["A living room with wooden floors and exactly one white wall."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:214859", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000249129.jpg", "positive_caption": ["The room is full of a number of stuffed animals arranged in chairs."], "negative_caption": ["The room is full of a single stuffed animal arranged in chairs."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:117915", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000275791.jpg", "positive_caption": ["A number of covered boats are in the water by the shore."], "negative_caption": ["Exactly one covered boat is in the water by the shore."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:415894", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000019402.jpg", "positive_caption": ["Some people with heavy winter coats are eating"], "negative_caption": ["Exactly one person with heavy winter coats is eating"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:551900", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000183104.jpg", "positive_caption": ["Some giraffes stick their heads out and get their picture taken."], "negative_caption": ["A single giraffe stickes its head out and get its picture taken."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:117801", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000315257.jpg", "positive_caption": ["A bird with some outstretched blue wings is sitting on some bird feeder."], "negative_caption": ["A bird with exactly one outstretched blue wing is sitting on some bird feeder."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:710900", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000073533.jpg", "positive_caption": ["A couple of kids in some yellow shirts are sitting together"], "negative_caption": ["A couple of kids in exactly one yellow shirt are sitting together"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:775892", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000107226.jpg", "positive_caption": ["The man is riding a bike led by some dogs."], "negative_caption": ["The man is riding a bike led by a single dog."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:212427", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000350023.jpg", "positive_caption": ["A long road with cars on some sides of it"], "negative_caption": ["A long road with cars on exactly one side of it"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:682645", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000076625.jpg", "positive_caption": ["A number of people are walking by a blue train next to a mountain."], "negative_caption": ["A single person is walking by a blue train next to a mountain."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:297060", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000229753.jpg", "positive_caption": ["Some giraffes are standing next to a tree trunk."], "negative_caption": ["Exactly one giraffe is standing next to a tree trunk."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:612492", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000244592.jpg", "positive_caption": ["A number of zebras socialize on some rocks in an artificial habitat."], "negative_caption": ["Exactly one zebra socializes on some rocks in an artificial habitat."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:90541", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000119641.jpg", "positive_caption": ["A number of people are riding on elephants in a river."], "negative_caption": ["A single person is riding on elephants in a river."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:213119", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000273715.jpg", "positive_caption": ["A number of people are standing under the arch for a ski race"], "negative_caption": ["A single person is standing under the arch for a ski race"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:567227", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000201426.jpg", "positive_caption": ["Some young boys are enjoying pizza and pepsi"], "negative_caption": ["Exactly one young boy is enjoying pizza and pepsi"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:631499", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000571857.jpg", "positive_caption": ["A number of people are camping out in the desert"], "negative_caption": ["A single person is camping out in the desert"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:98324", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000555597.jpg", "positive_caption": ["A number of cars parked on a city street with tall buildings in the background."], "negative_caption": ["A single car parked on a city street with tall buildings in the background."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:149093", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000205324.jpg", "positive_caption": ["A number of men are playing a game of frisbee on the field."], "negative_caption": ["A single man is playing a game of frisbee on the field."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:517015", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000391722.jpg", "positive_caption": ["A man presents a cake with some lit candles on it to a seated man."], "negative_caption": ["A man presents a cake with exactly one lit candle on it to a seated man."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:432058", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000429690.jpg", "positive_caption": ["A guy playing baseball with some people watching from the stands."], "negative_caption": ["A guy playing baseball with exactly one person watching from the stands."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:200617", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000581206.jpg", "positive_caption": ["An image of a person holding some hotdogs in a platter"], "negative_caption": ["An image of a person holding exactly one hotdog in a platter"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:156932", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000114884.jpg", "positive_caption": ["A number of buses lined up letting people aboard them."], "negative_caption": ["A single bus lined up letting people aboard it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:531966", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000289516.jpg", "positive_caption": ["A clock sits above some green bushes under a blue sky."], "negative_caption": ["A clock sits above a single green bush under a blue sky."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:8468", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000097230.jpg", "positive_caption": ["A number of elephants seem to be roaming in the wild."], "negative_caption": ["A single elephant seems to be roaming in the wild."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:358626", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000434996.jpg", "positive_caption": ["A kitten sleeps with a number of stuffed animals on the bed."], "negative_caption": ["A kitten sleeps with exactly one stuffed animal on the bed."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:312634", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000512929.jpg", "positive_caption": ["Two young girls are cooking a number of green beans on the stove."], "negative_caption": ["Two young girls are cooking exactly one green bean on the stove."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:381015", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000034257.jpg", "positive_caption": ["Baskets are displaying carrots, some leafy greens, and other vegetables."], "negative_caption": ["Baskets are displaying carrots, a single leafy green, and other vegetables."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:88681", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000057232.jpg", "positive_caption": ["A chair is fashioned from a number of baseball bats and two cushions."], "negative_caption": ["A chair is fashioned from exactly one baseball bat and two cushions."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:151034", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000184338.jpg", "positive_caption": ["A truck with a number of painted decorations is parked in a desert."], "negative_caption": ["A truck with a single painted decoration is parked in a desert."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:280597", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000559099.jpg", "positive_caption": ["A number of cows graze peacefully in a field with a dormant volcano in the distance."], "negative_caption": ["Exactly one cow grazes peacefully in a field with a dormant volcano in the distance."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:659964", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000457559.jpg", "positive_caption": ["There are a number of people running in the grass playing soccer"], "negative_caption": ["There is a single person running in the grass playing soccer"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:172870", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000526392.jpg", "positive_caption": ["A number of cars sit parked on the side of a street."], "negative_caption": ["Exactly one car sits parked on the side of a street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:817572", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000080659.jpg", "positive_caption": ["A group of jockeys ride some horses on a track."], "negative_caption": ["A group of jockeys ride a single horse on a track."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:374450", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000290768.jpg", "positive_caption": ["Some mugs are on the kitchen counter of a stove."], "negative_caption": ["A single mug is on the kitchen counter of a stove."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:473982", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000331569.jpg", "positive_caption": ["A number of strawberries sit on a plate next to a milkshake."], "negative_caption": ["A single strawberry sits on a plate next to a milkshake."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:449200", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000326541.jpg", "positive_caption": ["People at a public event using some cell phones to take pictures of the event."], "negative_caption": ["People at a public event using a single cell phone to take pictures of the event."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:106692", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000570756.jpg", "positive_caption": ["Several people are flying some kites on the beach."], "negative_caption": ["Several people are flying a single kite on the beach."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:292887", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000194832.jpg", "positive_caption": ["An empty bus with some brown cloth covered seats."], "negative_caption": ["An empty bus with a single brown cloth covered seat."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:95656", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000047769.jpg", "positive_caption": ["The small room has a couch, a television, and a table with some stools."], "negative_caption": ["The small room has a couch, a television, and a table with a single stool."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:637339", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000481582.jpg", "positive_caption": ["There are a number of people standing next to a horse."], "negative_caption": ["There is exactly one person standing next to a horse."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:575496", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000420916.jpg", "positive_caption": ["Three people are sitting on a bench looking out at a number of mountains and a lake."], "negative_caption": ["Three people are sitting on a bench looking out at exactly one mountain and a lake."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:664763", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000459500.jpg", "positive_caption": ["The statue of a number of pelicans has a clock above it."], "negative_caption": ["The statue of a single pelican has a clock above it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:258102", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000130826.jpg", "positive_caption": ["Some elder people sit on a bench on a bus street"], "negative_caption": ["A single elder person sits on a bench on a bus street"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:185306", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000238866.jpg", "positive_caption": ["There are some donuts layed to dry on a grill"], "negative_caption": ["There is exactly one donut layed to dry on a grill"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:150976", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000224807.jpg", "positive_caption": ["A number of men sit around a table sharing a meal."], "negative_caption": ["A single man sits around a table sharing a meal."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:343061", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000577735.jpg", "positive_caption": ["A small copper vase with some flowers in it"], "negative_caption": ["A small copper vase with exactly one flower in it"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:551663", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000507575.jpg", "positive_caption": ["This computer desk has a number of laptops and a printer sitting on it."], "negative_caption": ["This computer desk has exactly one laptop and a printer sitting on it."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:623651", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000329614.jpg", "positive_caption": ["A bus and some other cars are traveling on a street."], "negative_caption": ["A bus and a single other car are traveling on a street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:451966", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000570456.jpg", "positive_caption": ["A living room with some seating areas, tables, and windows."], "negative_caption": ["A living room with exactly one seating area, tables, and windows."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:196661", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000162732.jpg", "positive_caption": ["A number of soccer players are having a confrontation"], "negative_caption": ["Exactly one soccer player is having a confrontation"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:391214", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000472046.jpg", "positive_caption": ["A kitchen with a stove, sink, table, chairs and some couches."], "negative_caption": ["A kitchen with a stove, sink, table, chairs and a single couch."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:494622", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000104603.jpg", "positive_caption": ["A bear walks through tall grass near some trees."], "negative_caption": ["A bear walks through tall grass near exactly one tree."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:674017", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000385719.jpg", "positive_caption": ["An office desk with a number of computer monitors and one laptop."], "negative_caption": ["An office desk with exactly one computer monitor and one laptop."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:434339", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000371677.jpg", "positive_caption": ["This computer set up has a number of monitors and an ergonomic keyboard."], "negative_caption": ["This computer set up has exactly one monitor and an ergonomic keyboard."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:606362", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000300341.jpg", "positive_caption": ["Some men play the nintendo wii console while others watch"], "negative_caption": ["Exactly one man plays the nintendo wii console while others watch"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:583790", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000423617.jpg", "positive_caption": ["A number of buses and a taxi go down a street,"], "negative_caption": ["Exactly one bus and a taxi goes down a street,"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:69969", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000500270.jpg", "positive_caption": ["People skateboard around a skate park near a number of rails."], "negative_caption": ["People skateboard around a skate park near a single rail."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:393136", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000156924.jpg", "positive_caption": ["A man and a woman are holding some video game controllers"], "negative_caption": ["A man and a woman are holding exactly one video game controller"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:629949", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000222559.jpg", "positive_caption": ["There are some boats in the water that you can see from the beach."], "negative_caption": ["There is exactly one boat in the water that you can see from the beach."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:300188", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000333772.jpg", "positive_caption": ["Some black and white cats are on a keyboard."], "negative_caption": ["A single black and white cat is on a keyboard."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:535457", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000297427.jpg", "positive_caption": ["A man holding a cheeseburger made out of a number of donuts."], "negative_caption": ["A man holding a cheeseburger made out of exactly one donut."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:714759", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000169996.jpg", "positive_caption": ["Two people are riding some bikes through the street traffic."], "negative_caption": ["Two people are riding a single bike through the street traffic."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:490138", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000102411.jpg", "positive_caption": ["Some people are riding a motorcycle on the beach."], "negative_caption": ["A single person is riding a motorcycle on the beach."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:61028", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000061171.jpg", "positive_caption": ["A number of cows and ponies are eating hay in the barn"], "negative_caption": ["Exactly one cow and ponies is eating hay in the barn"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:784346", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000548780.jpg", "positive_caption": ["A number of people sit on a bench with pigeons and other people nearby."], "negative_caption": ["A single person sits on a bench with pigeons and other people nearby."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:144286", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000333772.jpg", "positive_caption": ["Some cats are laying on the keyboard of a computer."], "negative_caption": ["A single cat is laying on the keyboard of a computer."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:529970", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000413404.jpg", "positive_caption": ["A park with a number of benches and lots of trees."], "negative_caption": ["A park with a single bench and lots of trees."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:737602", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000511999.jpg", "positive_caption": ["Some rail workers stand on a platform where a train is waiting."], "negative_caption": ["A single rail worker stands on a platform where a train is waiting."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:828280", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000413404.jpg", "positive_caption": ["Some park benches with a brown fence in the background and trees overhead."], "negative_caption": ["A single park bench with a brown fence in the background and trees overhead."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:741880", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000431876.jpg", "positive_caption": ["Some mounted police officers and their horses line up on the street."], "negative_caption": ["A single mounted police officer and its horse lines up on the street."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:281963", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000104669.jpg", "positive_caption": ["The plate is full of broccoli, some potatoes, and meat."], "negative_caption": ["The plate is full of broccoli, a single potato, and meat."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:397367", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000301563.jpg", "positive_caption": ["A man riding some skis down a snow covered slope."], "negative_caption": ["A man riding a single ski down a snow covered slope."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:784868", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000255165.jpg", "positive_caption": ["A desk filled with some paperwork, a laptop and a computer with a number of monitors"], "negative_caption": ["A desk filled with some paperwork, a laptop and a computer with a single monitor"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:761383", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000203389.jpg", "positive_caption": ["Several men stand next to other men as they sit on a number of motorcycles."], "negative_caption": ["Several men stand next to other men as they sit on a single motorcycle."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:746850", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000290833.jpg", "positive_caption": ["Some zebras graze in a field of short grass."], "negative_caption": ["A single zebra grazes in a field of short grass."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:53357", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000060770.jpg", "positive_caption": ["A couple of zebras are grazing next to some trees."], "negative_caption": ["A couple of zebras are grazing next to a single tree."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:342791", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000312237.jpg", "positive_caption": ["Some people are having fun on a crowded beach."], "negative_caption": ["Exactly one person is having fun on a crowded beach."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:73459", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000153229.jpg", "positive_caption": ["Some disc players leap to catch the disc"], "negative_caption": ["A single disc player leaps to catch the disc"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:744642", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000319369.jpg", "positive_caption": ["A number of beach goers set up umbrellas next to rental signs while a cop watches."], "negative_caption": ["Exactly one beach goer set up umbrellas next to rental signs while a cop watches."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:122922", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000530836.jpg", "positive_caption": ["An old advertisement shows a large kitchen with white cabinets and appliances and a number of yellow walls."], "negative_caption": ["An old advertisement shows a large kitchen with white cabinets and appliances and exactly one yellow wall."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:560072", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000032334.jpg", "positive_caption": ["A number of people, a man and a woman, are toasting with wine glasses."], "negative_caption": ["Exactly one person, a man and a woman, is toasting with wine glasses."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:56733", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000376310.jpg", "positive_caption": ["A purple bathroom with three sinks and a purple countertop with a mirror surrounded with some light bulbs."], "negative_caption": ["A purple bathroom with three sinks and a purple countertop with a mirror surrounded with exactly one light bulb."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:299533", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000007795.jpg", "positive_caption": ["A large modern hotel room with a number of double beds"], "negative_caption": ["A large modern hotel room with a single double bed"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:336221", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000109118.jpg", "positive_caption": ["Three men are dressed in some baseball uniforms and are posed for a portrait."], "negative_caption": ["Three men are dressed in exactly one baseball uniform and are posed for a portrait."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:825693", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000309964.jpg", "positive_caption": ["A number of people are sitting outside under a large umbrella."], "negative_caption": ["Exactly one person is sitting outside under a large umbrella."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:650635", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000335081.jpg", "positive_caption": ["Two teddy bears are seated with a number of other stuffed animals."], "negative_caption": ["Two teddy bears are seated with exactly one other stuffed animal."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:276685", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000186632.jpg", "positive_caption": ["The large bathroom has some sinks and a chandelier."], "negative_caption": ["The large bathroom has a single sink and a chandelier."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:410660", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000384468.jpg", "positive_caption": ["There are a number of people riding on an elephant back"], "negative_caption": ["There is a single person riding on an elephant back"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:195073", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000457884.jpg", "positive_caption": ["Some children are playing baseball outside in a field."], "negative_caption": ["A single child is playing baseball outside in a field."], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:213046", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000534827.jpg", "positive_caption": ["A number of people riding some motorbikes on the road"], "negative_caption": ["A single person riding some motorbikes on the road"], "original_file_name": "plurals", "dataset": "coco2017", "key": "plurals:coco2017:315014", "linguistic_phenomena": "plurals", "original_split": "val"}
{"image_file_name": "coco2017/000000462576.jpg", "positive_caption": ["Breakfast items including juice are on the table."], "negative_caption": ["Breakfast items including juice are off the table."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:212732", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000294162.jpg", "positive_caption": ["The white laptop is turned off but left open."], "negative_caption": ["The white laptop is turned on but left open."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:528685", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000144333.jpg", "positive_caption": ["a girl is sitting on a bicycle outside"], "negative_caption": ["A girl is sitting behind a bicycle outside"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:646131", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000181666.jpg", "positive_caption": ["The nomadic sheepherd walks behind a large group of livestock in their desert habitat."], "negative_caption": ["The nomadic sheepherd walks on a large group of livestock in their desert habitat."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:53860", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000482436.jpg", "positive_caption": ["The woman in the diner and the man looking into the window are making eye contact."], "negative_caption": ["The woman outside the diner and the man looking into the window are making eye contact."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:425574", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000153299.jpg", "positive_caption": ["two giraffes are standing together outside a barn"], "negative_caption": ["Two giraffes are standing together in a barn"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:538080", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000337055.jpg", "positive_caption": ["a woman with a tattoo is sitting on the train tracks"], "negative_caption": ["A woman with a tattoo is sitting behind the train tracks"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:672194", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000526728.jpg", "positive_caption": ["Two people smile while posing behind luggage suitcases on the sidewalk."], "negative_caption": ["Two people smile while posing in luggage suitcases on the sidewalk."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:709875", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000402519.jpg", "positive_caption": ["A yellow and red bird is sitting in a tree."], "negative_caption": ["A yellow and red bird is sitting behind a tree."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:538176", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000490413.jpg", "positive_caption": ["The airplane has landed behind a fence with barbed wire"], "negative_caption": ["The airplane has landed on a fence with barbed wire"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:527615", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000178618.jpg", "positive_caption": ["an elephant is standing in a dirt field"], "negative_caption": ["An elephant is standing beside a dirt field"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:609565", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000140286.jpg", "positive_caption": ["A horse and carriage parked beside a building."], "negative_caption": ["A horse and carriage parked in a building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:507095", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000033368.jpg", "positive_caption": ["A tennis player is standing on the court."], "negative_caption": ["A tennis player is standing off the court."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:464107", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000034760.jpg", "positive_caption": ["Cleaning products are on the counter of the bathroom."], "negative_caption": ["Cleaning products are beneath the counter of the bathroom."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:491321", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000320554.jpg", "positive_caption": ["A black cat sits beneath a bench in the sun."], "negative_caption": ["A black cat sits on a bench in the sun."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:664739", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000141671.jpg", "positive_caption": ["Horses are racing next to motorcycles on a dirt track."], "negative_caption": ["Horses are racing next to motorcycles off a dirt track."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:193101", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000068628.jpg", "positive_caption": ["Guy jumps off the steps doing a flip trick with his skateboard"], "negative_caption": ["Guy jumps on the steps doing a flip trick with his skateboard"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:392059", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000003255.jpg", "positive_caption": ["A group of skiers have left a trail through the snow on the mountain."], "negative_caption": ["A group of skiers have left a trail through the snow off the mountain."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:729764", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000336628.jpg", "positive_caption": ["A man in a clown suit is stepping off a trolley."], "negative_caption": ["A man in a clown suit is stepping on a trolley."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:24786", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000199681.jpg", "positive_caption": ["A stuffed rabbit has been placed inside of a microwave oven."], "negative_caption": ["A stuffed rabbit has been placed out of a microwave oven."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:161493", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000512248.jpg", "positive_caption": ["A clock outside a building says the time is 4:30"], "negative_caption": ["A clock inside a building says the time is 4 : 30"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:818612", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000005586.jpg", "positive_caption": ["A tennis player in a crowded arena waits for the next volley."], "negative_caption": ["A tennis player outside a crowded arena waits for the next volley."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:783975", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000289938.jpg", "positive_caption": ["A hot dog vendor sits outside a famous building in the city."], "negative_caption": ["A hot dog vendor sits in a famous building in the city."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:709457", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000338624.jpg", "positive_caption": ["A man is walking a dog on a sidewalk."], "negative_caption": ["A man is walking a dog off a sidewalk."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:746721", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000179487.jpg", "positive_caption": ["The woman is on the court playing a game of tennis."], "negative_caption": ["The woman is off the court playing a game of tennis."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:494204", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000336628.jpg", "positive_caption": ["A clown dressed in a suit bedecked with dinosaurs steps off a cable car."], "negative_caption": ["A clown dressed in a suit bedecked with dinosaurs steps on a cable car."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:22899", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000194471.jpg", "positive_caption": ["A man on a skateboard is coming up a ramp."], "negative_caption": ["A man on a skateboard is coming down a ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:206259", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000465675.jpg", "positive_caption": ["There is a tractor next to some boats on the beach"], "negative_caption": ["There is a tractor next to some boats off the beach"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:329120", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000185472.jpg", "positive_caption": ["The train is approaching and a man is getting off his bicycle."], "negative_caption": ["The train is approaching and a man is getting on his bicycle."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:136266", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000273711.jpg", "positive_caption": ["there are many different types of food gathered on the table"], "negative_caption": ["There are many different types of food gathered under the table"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:277591", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000320554.jpg", "positive_caption": ["A cat sits under a park bench outside."], "negative_caption": ["A cat sits on a park bench outside."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:664751", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000226417.jpg", "positive_caption": ["Several motorcycles are parked at a red light in the road in a city with tall buildings."], "negative_caption": ["Several motorcycles are parked at a red light off the road in a city with tall buildings."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:501300", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000239274.jpg", "positive_caption": ["A pontoon boat ferry full of passengers pushes off from shore."], "negative_caption": ["A pontoon boat ferry full of passengers pushes in from shore."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:445772", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000563267.jpg", "positive_caption": ["Two men are in a building with brick walls."], "negative_caption": ["Two men are behind a building with brick walls."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:21771", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000393226.jpg", "positive_caption": ["The man is walking behind the concession bus."], "negative_caption": ["The man is walking down the concession bus."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:529862", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000423123.jpg", "positive_caption": ["A young oerson is raiding a small fridge in their room."], "negative_caption": ["A young oerson is raiding a small fridge outside their room."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:502879", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000289938.jpg", "positive_caption": ["The food cart is right outside the arena,"], "negative_caption": ["The food cart is right in the arena,"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:698393", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000257624.jpg", "positive_caption": ["The young child is standing beside two soccer balls."], "negative_caption": ["The young child is standing on two soccer balls."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:711152", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000089880.jpg", "positive_caption": ["Two dogs are playing together on the grass"], "negative_caption": ["Two dogs are playing together under the grass"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:7721", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000517687.jpg", "positive_caption": ["two cellphones are sitting side by side on the table."], "negative_caption": ["Two cellphones are sitting side by side under the table."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:737622", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000512648.jpg", "positive_caption": ["a brown cow is standing under a green tree"], "negative_caption": ["A brown cow is standing on a green tree"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:371904", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000116825.jpg", "positive_caption": ["A cat plays with a pocket knife on a table."], "negative_caption": ["A cat plays with a pocket knife underneath a table."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:67819", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000110638.jpg", "positive_caption": ["a small elephant walks underneath a big elephant"], "negative_caption": ["A small elephant walks beside a big elephant"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:362442", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000086956.jpg", "positive_caption": ["a guy holds a bat and put it on a girl's head."], "negative_caption": ["A guy holds a bat and put it under a girl's head."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:251237", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000367195.jpg", "positive_caption": ["A picture of a dog laying under a table on the rug."], "negative_caption": ["A picture of a dog laying at a table on the rug."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:270353", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000061268.jpg", "positive_caption": ["A train carrying freight containers is on the tracks."], "negative_caption": ["A train carrying freight containers is under the tracks."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:686203", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000563603.jpg", "positive_caption": ["A group of giraffes gather under a tree."], "negative_caption": ["A group of giraffes gather on a tree."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:361808", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000035682.jpg", "positive_caption": ["A plate of donuts on a tray sitting on a table in a bakery."], "negative_caption": ["A plate of donuts on a tray sitting on a table near a bakery."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:670788", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000267191.jpg", "positive_caption": ["Two people are riding elephants beside some trees."], "negative_caption": ["Two people are riding elephants on some trees."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:435390", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000429281.jpg", "positive_caption": ["There are many bananas sitting on the shelf."], "negative_caption": ["There are many bananas sitting under the shelf."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:575495", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000139871.jpg", "positive_caption": ["Someone has crawled under the plane to check that everything is operational."], "negative_caption": ["Someone has crawled in the plane to check that everything is operational."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:624602", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000263594.jpg", "positive_caption": ["This is a picture of a car parked in a handicap space in a lot."], "negative_caption": ["This is a picture of a car parked in a handicap space outside a lot."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:639923", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000507037.jpg", "positive_caption": ["A group of people visit and eat food outside city hall."], "negative_caption": ["A group of people visit and eat food in city hall."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:511203", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000465806.jpg", "positive_caption": ["A person reaches for a container on a counter."], "negative_caption": ["A person reaches for a container under a counter."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:548729", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000411953.jpg", "positive_caption": ["a guy plays guitar on the stage center"], "negative_caption": ["A guy plays guitar off the stage center"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:790277", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000407868.jpg", "positive_caption": ["This youngster tries to get his kite off the ground"], "negative_caption": ["This youngster tries to get his kite on the ground"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:298898", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000106330.jpg", "positive_caption": ["There is a stuffed bear on a white floor"], "negative_caption": ["There is a stuffed bear under a white floor"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:159692", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000147745.jpg", "positive_caption": ["Two trucks parked next to each other on a dirt road."], "negative_caption": ["Two trucks parked next to each other off a dirt road."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:801527", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000050896.jpg", "positive_caption": ["There is a big bowl of oranges on the counter."], "negative_caption": ["There is a big bowl of oranges under the counter."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:590163", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000197870.jpg", "positive_caption": ["A chicken is standing under a bench in a park."], "negative_caption": ["A chicken is standing on a bench in a park."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:612167", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000122046.jpg", "positive_caption": ["A woman poses for a photo as she sits on a chair with an umbrella"], "negative_caption": ["A woman poses for a photo as she sits behind a chair with an umbrella"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:418199", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000118209.jpg", "positive_caption": ["there are two horses standing behind a fence"], "negative_caption": ["There are two horses standing on a fence"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:672972", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000107094.jpg", "positive_caption": ["A man riding skis on top of snow covered ground."], "negative_caption": ["A man riding skis off top of snow covered ground."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:606602", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000485844.jpg", "positive_caption": ["A housewife holds a platter of food in the kitchen."], "negative_caption": ["A housewife holds a platter of food outside the kitchen."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:652957", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000437514.jpg", "positive_caption": ["There is a park bench outside a store with a potted tree next to it."], "negative_caption": ["There is a park bench in a store with a potted tree next to it."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:777296", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000027620.jpg", "positive_caption": ["The laptop was left open on the desk."], "negative_caption": ["The laptop was left open under the desk."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:391631", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000485895.jpg", "positive_caption": ["A giraffe stands under a tree in a grassy place."], "negative_caption": ["A giraffe stands on a tree in a grassy place."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:192331", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000386277.jpg", "positive_caption": ["A photo of an orange growing on a tree."], "negative_caption": ["A photo of an orange growing under a tree."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:375806", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000273715.jpg", "positive_caption": ["three people are standing under the arch for a ski race"], "negative_caption": ["Three people are standing in the arch for a ski race"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:567227", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000400815.jpg", "positive_caption": ["A man is sitting in the flatbed of a truck."], "negative_caption": ["A man is sitting beside the flatbed of a truck."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:727062", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000412240.jpg", "positive_caption": ["A small black dog sits beside a pair of shoes."], "negative_caption": ["A small black dog sits on a pair of shoes."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:607681", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000416170.jpg", "positive_caption": ["a cat is sitting in a window that has a dirty exterior"], "negative_caption": ["A cat is sitting under a window that has a dirty exterior"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:552726", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000161397.jpg", "positive_caption": ["Several displays of flowers are on a table."], "negative_caption": ["Several displays of flowers are behind a table."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:714469", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000237984.jpg", "positive_caption": ["A green chair is sitting behind a green bench."], "negative_caption": ["A green chair is sitting on a green bench."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:502445", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000512648.jpg", "positive_caption": ["A cow is standing underneath a leaning tree."], "negative_caption": ["A cow is standing on a leaning tree."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:371439", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000099182.jpg", "positive_caption": ["a man is flipping through a book on a bed"], "negative_caption": ["A man is flipping through a book under a bed"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:578298", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000110638.jpg", "positive_caption": ["A baby elephant is walking under a larger elephant."], "negative_caption": ["A baby elephant is walking on a larger elephant."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:367995", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000060449.jpg", "positive_caption": ["A laptop computer is on a glass table on a balcony."], "negative_caption": ["A laptop computer is under a glass table on a balcony."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:714340", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000198641.jpg", "positive_caption": ["A cat is on a desk looking at the computer screens."], "negative_caption": ["A cat is under a desk looking at the computer screens."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:572532", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000210789.jpg", "positive_caption": ["The two people are standing under an umbrella in the rain."], "negative_caption": ["The two people are standing on an umbrella in the rain."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:538759", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000378873.jpg", "positive_caption": ["Fruits and vegetables are being sold in a market."], "negative_caption": ["Fruits and vegetables are being sold outside a market."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:145149", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000076417.jpg", "positive_caption": ["A dog is sticking it head outside of a car window"], "negative_caption": ["A dog is sticking it head in of a car window"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:589396", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000256192.jpg", "positive_caption": ["a bright yellow police motorcycle parkd in the road"], "negative_caption": ["A bright yellow police motorcycle parkd off the road"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:790107", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000199977.jpg", "positive_caption": ["An airplane is letting off white smoke against a blue sky."], "negative_caption": ["An airplane is letting in white smoke against a blue sky."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:356722", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000262227.jpg", "positive_caption": ["A computer is lit up on the checkout counter."], "negative_caption": ["A computer is lit down on the checkout counter."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:600056", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000517832.jpg", "positive_caption": ["The black dog sits alertly on the vintage chair."], "negative_caption": ["The black dog sits alertly behind the vintage chair."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:77288", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000382122.jpg", "positive_caption": ["A church with a clock stands behind a fence"], "negative_caption": ["A church with a clock stands on a fence"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:85904", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000185157.jpg", "positive_caption": ["The bikes are all parked beside the sign."], "negative_caption": ["The bikes are all parked underneath the sign."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:196616", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000384666.jpg", "positive_caption": ["A group of young children riding skis down a snow covered mountain."], "negative_caption": ["A group of young children riding skis up a snow covered mountain."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:117231", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000247806.jpg", "positive_caption": ["We are looking up at an old clock tower."], "negative_caption": ["We are looking down at an old clock tower."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:761396", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000338901.jpg", "positive_caption": ["a brown white and black dog is laying on a gray couch"], "negative_caption": ["A brown white and black dog is laying behind a gray couch"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:566695", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000170739.jpg", "positive_caption": ["a couple of elephants are standing behind a fence"], "negative_caption": ["A couple of elephants are standing on a fence"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:597199", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000323355.jpg", "positive_caption": ["A boy wearing yellow is holding a pizza in a box."], "negative_caption": ["A boy wearing yellow is holding a pizza outside a box."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:598468", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000217948.jpg", "positive_caption": ["Three brown bears are looking outside their enclosure."], "negative_caption": ["Three brown bears are looking in their enclosure."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:116933", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000246968.jpg", "positive_caption": ["A young woman standing in the kitchen pours from a large measuring cup."], "negative_caption": ["A young woman standing outside the kitchen pours from a large measuring cup."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:692352", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000370042.jpg", "positive_caption": ["There are many vases on display outside the building."], "negative_caption": ["There are many vases on display in the building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:591519", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000290619.jpg", "positive_caption": ["A banana is sitting beside a large bowl storage container."], "negative_caption": ["A banana is sitting on a large bowl storage container."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:266228", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000119038.jpg", "positive_caption": ["Three cows stand in a pasture on a mountain."], "negative_caption": ["Three cows stand outside a pasture on a mountain."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:596386", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000259830.jpg", "positive_caption": ["A scooter and bicycles are parked outside a local business."], "negative_caption": ["A scooter and bicycles are parked in a local business."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:633148", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000245764.jpg", "positive_caption": ["a black and gray cat is sitting on a toilet"], "negative_caption": ["A black and gray cat is sitting behind a toilet"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:370621", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000527750.jpg", "positive_caption": ["There is a man standing in the kitchen."], "negative_caption": ["There is a man standing beside the kitchen."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:815306", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000430961.jpg", "positive_caption": ["A baseball player lunges and reaches back with the ball."], "negative_caption": ["A baseball player lunges and reaches up with the ball."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:769279", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000478393.jpg", "positive_caption": ["Teddybear, kitten and calico cat are all taking a nap on the bed."], "negative_caption": ["Teddybear, kitten and calico cat are all taking a nap beside the bed."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:606492", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000481567.jpg", "positive_caption": ["An older man is standing beside a red motorcycle."], "negative_caption": ["An older man is standing on a red motorcycle."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:306127", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000338624.jpg", "positive_caption": ["A man walks a dog past rows of chairs outside a store."], "negative_caption": ["A man walks a dog past rows of chairs in a store."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:748601", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000116439.jpg", "positive_caption": ["A person sits in a small boat on the water."], "negative_caption": ["A person sits beside a small boat on the water."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:745202", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000296649.jpg", "positive_caption": ["people ride their motorcycles beside some cars, passing by an empty street with stores and apartment buildings"], "negative_caption": ["People ride their motorcycles in some cars, passing by an empty street with stores and apartment buildings"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:681470", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000376442.jpg", "positive_caption": ["There is a stuffed animal sitting on the toliet."], "negative_caption": ["There is a stuffed animal sitting beside the toliet."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:482454", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000319721.jpg", "positive_caption": ["A woman stands beside a large brown horse."], "negative_caption": ["A woman stands on a large brown horse."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:164414", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000427655.jpg", "positive_caption": ["A horse drawn carriage with two women riding on it."], "negative_caption": ["A horse drawn carriage with two women riding behind it."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:545724", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000106235.jpg", "positive_caption": ["There is a cream colored couch behind the oval coffee table."], "negative_caption": ["There is a cream colored couch on the oval coffee table."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:479887", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000165336.jpg", "positive_caption": ["Two giraffe and a zebra are standing in a field."], "negative_caption": ["Two giraffe and a zebra are standing beside a field."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:247811", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000555012.jpg", "positive_caption": ["The roll of toilet paper beside the toilet is empty."], "negative_caption": ["The roll of toilet paper on the toilet is empty."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:711061", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000482487.jpg", "positive_caption": ["Two small clocks sit behind a glass window."], "negative_caption": ["Two small clocks sit outside a glass window."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:762872", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000488385.jpg", "positive_caption": ["A black and white motorcycle parked on the sidewalk outside a store."], "negative_caption": ["A black and white motorcycle parked on the sidewalk in a store."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:574284", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000089078.jpg", "positive_caption": ["A person is snowboarding slowly down a covered hill."], "negative_caption": ["A person is snowboarding slowly up a covered hill."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:767435", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000491008.jpg", "positive_caption": ["A man and a woman holding up a pizza in a seating area."], "negative_caption": ["A man and a woman holding down a pizza in a seating area."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:267879", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000578922.jpg", "positive_caption": ["A vase full of red flowers sits in a room with red walls and red decorations."], "negative_caption": ["A vase full of red flowers sits outside a room with red walls and red decorations."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:42606", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000368212.jpg", "positive_caption": ["A toddler sits on a toilet while brushing his teeth."], "negative_caption": ["A toddler sits behind a toilet while brushing his teeth."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:15971", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000272566.jpg", "positive_caption": ["A man and young girl sit behind a display of fruits."], "negative_caption": ["A man and young girl sit on a display of fruits."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:309590", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000460229.jpg", "positive_caption": ["There is a truck behind the stop sign."], "negative_caption": ["There is a truck on the stop sign."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:539197", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000061747.jpg", "positive_caption": ["there is a woman about to ski down a hill"], "negative_caption": ["There is a woman about to ski over a hill"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:41331", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000578871.jpg", "positive_caption": ["A young child holds up her bowl with a spoon in it."], "negative_caption": ["A young child holds down her bowl with a spoon in it."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:465736", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000352684.jpg", "positive_caption": ["A group of people gathered in the lobby of  a building."], "negative_caption": ["A group of people gathered outside the lobby of a building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:370541", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000052996.jpg", "positive_caption": ["Two woman soldiers talking to other women in a kitchen"], "negative_caption": ["Two woman soldiers talking to other women outside a kitchen"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:322128", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000511599.jpg", "positive_caption": ["Several people are standing outside a large boat."], "negative_caption": ["Several people are standing in a large boat."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:285024", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000091500.jpg", "positive_caption": ["The two teens are playing video games in the rec center."], "negative_caption": ["The two teens are playing video games outside the rec center."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:60078", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000293245.jpg", "positive_caption": ["A motorcycle parked outside the doors of a building"], "negative_caption": ["A motorcycle parked in the doors of a building"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:485123", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000520531.jpg", "positive_caption": ["A cat perches on a desk in a bedroom."], "negative_caption": ["A cat perches behind a desk in a bedroom."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:96662", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000245026.jpg", "positive_caption": ["A woman wearing glasses poses behind her birthday cake."], "negative_caption": ["A woman wearing glasses poses on her birthday cake."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:146535", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000261318.jpg", "positive_caption": ["A man on his phone is on a red bench."], "negative_caption": ["A man on his phone is behind a red bench."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:389066", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000319607.jpg", "positive_caption": ["A man is riding on bicycle alongside a new construction building."], "negative_caption": ["A man is riding on bicycle in a new construction building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:227490", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000465430.jpg", "positive_caption": ["Two sandwiches on Rye bread sit on a foil covered pan."], "negative_caption": ["Two sandwiches on rye bread sit beside a foil covered pan."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:597398", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000412240.jpg", "positive_caption": ["A puppy is sitting behind a pair of shoes."], "negative_caption": ["A puppy is sitting on a pair of shoes."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:600055", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000117914.jpg", "positive_caption": ["A toilet and towel rack are in a bathroom."], "negative_caption": ["A toilet and towel rack are above a bathroom."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:639634", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000226592.jpg", "positive_caption": ["Reading materials are stowed above a zebra themed bed for relaxation."], "negative_caption": ["Reading materials are stowed in a zebra themed bed for relaxation."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:159543", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000067310.jpg", "positive_caption": ["A young man skateboarding jumps on a concrete ramp."], "negative_caption": ["A young man skateboarding jumps over a concrete ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:653930", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000553990.jpg", "positive_caption": ["A woman riding a horse jumps over an obstacle."], "negative_caption": ["A woman riding a horse jumps onto an obstacle."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:680662", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000088218.jpg", "positive_caption": ["The street signs and traffic signal are below wires attached to the pole."], "negative_caption": ["The street signs and traffic signal are on wires attached to the pole."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:655811", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000376307.jpg", "positive_caption": ["there are two people that are standing in a farmers market"], "negative_caption": ["There are two people that are standing outside a farmers market"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:815821", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000410880.jpg", "positive_caption": ["A stuffed bear is sitting outside an eatery."], "negative_caption": ["A stuffed bear is sitting in an eatery."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:710090", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000375015.jpg", "positive_caption": ["The large bear is walking on a boulder."], "negative_caption": ["The large bear is walking behind a boulder."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:559487", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000101762.jpg", "positive_caption": ["A small cat is walking behind a bike."], "negative_caption": ["A small cat is walking on a bike."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:243276", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000078426.jpg", "positive_caption": ["A black cat is sitting on a desk."], "negative_caption": ["A black cat is sitting behind a desk."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:372634", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000244833.jpg", "positive_caption": ["there are two motorcycles that are parked behind seats"], "negative_caption": ["There are two motorcycles that are parked on seats"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:335821", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000506279.jpg", "positive_caption": ["There is a full glass sitting on the table."], "negative_caption": ["There is a full glass sitting beside the table."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:166796", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000255749.jpg", "positive_caption": ["A man stands beside a bus in a snowy forest at night."], "negative_caption": ["A man stands in a bus in a snowy forest at night."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:406722", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000411754.jpg", "positive_caption": ["A man checks his cell phone in a waiting area."], "negative_caption": ["A man checks his cell phone outside a waiting area."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:206220", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000242287.jpg", "positive_caption": ["A bicycle parked outside an old fashioned stone building."], "negative_caption": ["A bicycle parked in an old fashioned stone building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:488020", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000191580.jpg", "positive_caption": ["A plate of a prepared meal is lying on a table mat."], "negative_caption": ["A plate of a prepared meal is lying beside a table mat."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:755139", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000476810.jpg", "positive_caption": ["The black cat with white patches is sitting beside a remote control."], "negative_caption": ["The black cat with white patches is sitting on a remote control."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:659431", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000045472.jpg", "positive_caption": ["A pineapple and some oranges sit on a table."], "negative_caption": ["A pineapple and some oranges sit beside a table."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:458389", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000103548.jpg", "positive_caption": ["A man walking beside sheep on a country road."], "negative_caption": ["A man walking on sheep on a country road."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:65887", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000310862.jpg", "positive_caption": ["A man is frowning while standing in an empty room."], "negative_caption": ["A man is frowning while standing outside an empty room."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:760704", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000574810.jpg", "positive_caption": ["A cat is seated in a window sell looking outside the window"], "negative_caption": ["A cat is seated in a window sell looking in the window"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:34139", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000545958.jpg", "positive_caption": ["A cow stands on a sidewalk outside a building."], "negative_caption": ["A cow stands on a sidewalk in a building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:672540", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000258793.jpg", "positive_caption": ["I love the way the sun is creeping behind those two buidings"], "negative_caption": ["I love the way the sun is creeping on those two buidings"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:501134", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000236308.jpg", "positive_caption": ["The people are skiing down the snow covered hill."], "negative_caption": ["The people are skiing to the snow covered hill."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:243871", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000166747.jpg", "positive_caption": ["A group of people riding on a double decker bus on a bridge."], "negative_caption": ["A group of people riding beside a double decker bus on a bridge."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:4922", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000372466.jpg", "positive_caption": ["A computer mouse is beside a notebook computer."], "negative_caption": ["A computer mouse is in a notebook computer."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:729895", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000460333.jpg", "positive_caption": ["A little boy sits on a bed with a chair next to it."], "negative_caption": ["A little boy sits behind a bed with a chair next to it."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:616431", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000032901.jpg", "positive_caption": ["Four men are standing together behind a group of red chairs."], "negative_caption": ["Four men are standing together on a group of red chairs."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:180797", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000389109.jpg", "positive_caption": ["The personal sized pizza is on a table in the restaurant full of people."], "negative_caption": ["The personal sized pizza is on a table near the restaurant full of people."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:803523", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000060090.jpg", "positive_caption": ["A yellow train is pulling in to a train station."], "negative_caption": ["A yellow train is pulling out to a train station."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:113608", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000032038.jpg", "positive_caption": ["There is a fresh pizza that just came out the oven"], "negative_caption": ["There is a fresh pizza that just came in the oven"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:102506", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000301718.jpg", "positive_caption": ["there are two people sitting at a table eating"], "negative_caption": ["There are two people sitting under a table eating"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:497048", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000327617.jpg", "positive_caption": ["An older photo of a woman on a tennis court posing with her raquet."], "negative_caption": ["An older photo of a woman outside a tennis court posing with her raquet."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:442767", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000182441.jpg", "positive_caption": ["A man is standing outside of the water observing the huge flock of birds."], "negative_caption": ["A man is standing on of the water observing the huge flock of birds."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:817864", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000570782.jpg", "positive_caption": ["Three computers without screens sit on a desk."], "negative_caption": ["Three computers without screens sit beside a desk."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:187008", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000262631.jpg", "positive_caption": ["A large painted glossy vase sits on a table in a store."], "negative_caption": ["A large painted glossy vase sits behind a table in a store."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:225682", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000275392.jpg", "positive_caption": ["The child sits on the horse in the pasture."], "negative_caption": ["The child sits behind the horse in the pasture."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:9183", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000515266.jpg", "positive_caption": ["A truck and trailer sit behind a long bench."], "negative_caption": ["A truck and trailer sit on a long bench."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:118244", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000068093.jpg", "positive_caption": ["A woman is sitting on the passenger seat of a motorcycle."], "negative_caption": ["A woman is sitting behind the passenger seat of a motorcycle."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:733783", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000290592.jpg", "positive_caption": ["a bunch of sheep are standing behind a fence"], "negative_caption": ["A bunch of sheep are standing on a fence"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:616983", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000536038.jpg", "positive_caption": ["This girl is laying on the bed reading."], "negative_caption": ["This girl is laying beside the bed reading."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:523244", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000441553.jpg", "positive_caption": ["A crowd of people stand beside a train"], "negative_caption": ["A crowd of people stand on a train"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:169064", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000132375.jpg", "positive_caption": ["The small vase on the table is holding three flowers."], "negative_caption": ["The small vase beside the table is holding three flowers."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:570874", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000142238.jpg", "positive_caption": ["A group of people are holding other people on a soccer field."], "negative_caption": ["A group of people are holding other people outside a soccer field."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:218801", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000449432.jpg", "positive_caption": ["A group of people in military uniform stand outside a bus."], "negative_caption": ["A group of people in military uniform stand on a bus."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:673176", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000563702.jpg", "positive_caption": ["A fire fire truck parked in a parking lot."], "negative_caption": ["A fire fire truck parked beside a parking lot."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:672044", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000299887.jpg", "positive_caption": ["A man and woman beside a red motorcycle."], "negative_caption": ["A man and woman on a red motorcycle."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:682989", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000301421.jpg", "positive_caption": ["A computer is sitting on a home office work desk."], "negative_caption": ["A computer is sitting beside a home office work desk."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:53590", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000357737.jpg", "positive_caption": ["A man smiles while he stands beside a bike with a bike on it"], "negative_caption": ["A man smiles while he stands on a bike with a bike on it"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:147373", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000147740.jpg", "positive_caption": ["A lady walks down the street with bananas on her head"], "negative_caption": ["A lady walks down the street with bananas behind her head"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:102039", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000363207.jpg", "positive_caption": ["The bride and groom stand behind a square, multi-layer wedding cake."], "negative_caption": ["The bride and groom stand in a square, multi - layer wedding cake."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:620198", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000342295.jpg", "positive_caption": ["Someone put their art collection in their bath tub."], "negative_caption": ["Someone put their art collection behind their bath tub."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:394846", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000429690.jpg", "positive_caption": ["People look on as a ball heads towards a batter."], "negative_caption": ["People look on as a ball heads over a batter."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:211366", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000333745.jpg", "positive_caption": ["A woman holding an umbrella walks past the side of a bus with a large advertisement on the side."], "negative_caption": ["A woman holding an umbrella walks to the side of a bus with a large advertisement on the side."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:580115", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000521509.jpg", "positive_caption": ["A girl sits on the bed and photographs herself in the mirror with her tripod."], "negative_caption": ["A girl sits behind the bed and photographs herself in the mirror with her tripod."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:48957", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000263966.jpg", "positive_caption": ["A large grey horse is behind a wooden fence."], "negative_caption": ["A large grey horse is on a wooden fence."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:100774", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000360393.jpg", "positive_caption": ["A raw pizza with red peppers and cheese is on the counter."], "negative_caption": ["A raw pizza with red peppers and cheese is beside the counter."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:620150", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000467511.jpg", "positive_caption": ["A biker chic in high heel boots is talking to a man at a gas pump."], "negative_caption": ["A biker chic in high heel boots is talking over a man at a gas pump."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:242302", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000393093.jpg", "positive_caption": ["The train is going over the busy urban bridge."], "negative_caption": ["The train is going towards the busy urban bridge."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:647483", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000567197.jpg", "positive_caption": ["Trucks are parked outside of a market building."], "negative_caption": ["Trucks are parked inside of a market building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:664136", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000032861.jpg", "positive_caption": ["A young man stands inside with an umbrella pouring rain."], "negative_caption": ["A young man stands outside with an umbrella pouring rain."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:718975", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000231097.jpg", "positive_caption": ["A plate sits on a table mostly empty, except for a few vegetables."], "negative_caption": ["A plate sits beside a table mostly empty, except for a few vegetables."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:273906", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000299887.jpg", "positive_caption": ["a man and a woman are standing beside a red motorcycle"], "negative_caption": ["A man and a woman are standing on a red motorcycle"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:683301", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000196141.jpg", "positive_caption": ["A batter hits the ball in a baseball game."], "negative_caption": ["A batter hits the ball after a baseball game."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:62795", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000177383.jpg", "positive_caption": ["A train engine is on the railroad tracks."], "negative_caption": ["A train engine is behind the railroad tracks."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:745177", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000001675.jpg", "positive_caption": ["The large cat is resting comfortably behind the laptop screen."], "negative_caption": ["The large cat is resting comfortably on the laptop screen."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:274775", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000296284.jpg", "positive_caption": ["An assortment of doughnuts are arranged in a display case."], "negative_caption": ["An assortment of doughnuts are arranged under a display case."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:630640", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000233370.jpg", "positive_caption": ["A woman lies on the ground under a suitcase."], "negative_caption": ["A woman lies on the ground in a suitcase."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:619915", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000107087.jpg", "positive_caption": ["A black cat sits in a car and looks out."], "negative_caption": ["A black cat sits against a car and looks out."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:147561", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000181542.jpg", "positive_caption": ["A woman in white crosses the road against the flow of motorcycle traffic."], "negative_caption": ["A woman in white crosses the road in the flow of motorcycle traffic."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:581736", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000574823.jpg", "positive_caption": ["The men are playing baseball in the field."], "negative_caption": ["The men are playing baseball behind the field."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:43025", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000194746.jpg", "positive_caption": ["There is a pizza in the oven that has melted onto the bottom."], "negative_caption": ["There is a pizza under the oven that has melted onto the bottom."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:86131", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000108495.jpg", "positive_caption": ["A girl in an orange sweater is sitting on a skateboard."], "negative_caption": ["A girl in an orange sweater is sitting beside a skateboard."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:430594", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000119641.jpg", "positive_caption": ["People are riding on elephants in a river."], "negative_caption": ["People are riding on elephants beside a river."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:213119", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000010995.jpg", "positive_caption": ["The neatly made bed is beside an open window."], "negative_caption": ["The neatly made bed is in an open window."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:621630", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000164885.jpg", "positive_caption": ["A skier flies over a mogul on the slope."], "negative_caption": ["A skier flies to a mogul on the slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:234628", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000515445.jpg", "positive_caption": ["Surboarders are in the water and waiting on the shore."], "negative_caption": ["Surboarders are above the water and waiting on the shore."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:737806", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000359677.jpg", "positive_caption": ["A man is above the water enjoying some skiing."], "negative_caption": ["A man is in the water enjoying some skiing."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:366391", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000201072.jpg", "positive_caption": ["there is a male tennis player playing on the court"], "negative_caption": ["There is a male tennis player playing outside the court"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:692470", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000210394.jpg", "positive_caption": ["A bunch of people who are standing outside a bus."], "negative_caption": ["A bunch of people who are standing on a bus."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:570037", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000176232.jpg", "positive_caption": ["A bunch of flowers that are sitting in a vase."], "negative_caption": ["A bunch of flowers that are sitting over a vase."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:611697", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000308165.jpg", "positive_caption": ["A boy is jumping his skateboard over an orange cone."], "negative_caption": ["A boy is jumping his skateboard in an orange cone."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:675258", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000256195.jpg", "positive_caption": ["The train is on the tracks in the station."], "negative_caption": ["The train is on the tracks above the station."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:539139", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000207538.jpg", "positive_caption": ["A white microwave hangs above the oven under cabinets"], "negative_caption": ["A white microwave hangs in the oven under cabinets"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:414432", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000466416.jpg", "positive_caption": ["Large white buildings are lit up in the night."], "negative_caption": ["Large white buildings are lit down in the night."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:398149", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000556158.jpg", "positive_caption": ["A happy skier skis down a trail of fresh snow."], "negative_caption": ["A happy skier skis up a trail of fresh snow."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:129912", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000021903.jpg", "positive_caption": ["A man reaches out to give the elephant something."], "negative_caption": ["A man reaches inside to give the elephant something."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:112459", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000359937.jpg", "positive_caption": ["A large double decked bus parked in a lot."], "negative_caption": ["A large double decked bus parked beside a lot."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:94632", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000515266.jpg", "positive_caption": ["A large truck is parked beside an old, wooden bench."], "negative_caption": ["A large truck is parked in an old, wooden bench."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:116705", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000342397.jpg", "positive_caption": ["a young man wearing skis slides down the slope"], "negative_caption": ["A young man wearing skis slides up the slope"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:799384", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000025424.jpg", "positive_caption": ["A tennis player hits the ball up from the racket."], "negative_caption": ["A tennis player hits the ball down from the racket."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:555872", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000082807.jpg", "positive_caption": ["A dog is sitting in a chair at a table."], "negative_caption": ["A dog is sitting beside a chair at a table."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:676848", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000569700.jpg", "positive_caption": ["Flowers sit in a vase beside a tea pot."], "negative_caption": ["Flowers sit in a vase in a tea pot."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:624297", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000469828.jpg", "positive_caption": ["A man riding skis down a snow covered slope."], "negative_caption": ["A man riding skis up a snow covered slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:738763", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000538236.jpg", "positive_caption": ["Troisgros are piled up for sale at a busy market."], "negative_caption": ["Troisgros are piled down for sale at a busy market."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:136174", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000458054.jpg", "positive_caption": ["There is a row of used and broken toilets in a field."], "negative_caption": ["There is a row of used and broken toilets beside a field."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:451921", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000461751.jpg", "positive_caption": ["A man on a motorcycle driving beside a van."], "negative_caption": ["A man on a motorcycle driving in a van."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:669848", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000500613.jpg", "positive_caption": ["A fire truck sitting in the stations park lot."], "negative_caption": ["A fire truck sitting beside the stations park lot."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:817876", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000361730.jpg", "positive_caption": ["A large group of people flying kites beside a body of water"], "negative_caption": ["A large group of people flying kites in a body of water"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:618679", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000080413.jpg", "positive_caption": ["A small tan teddy bear is wedged into a spot on the dashboard of this car."], "negative_caption": ["A small tan teddy bear is wedged into a spot below the dashboard of this car."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:590207", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000197528.jpg", "positive_caption": ["A cat is sitting in the window in front of the window blinds."], "negative_caption": ["A cat is sitting beside the window in front of the window blinds."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:71093", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000308165.jpg", "positive_caption": ["A kid on skateboard jumps over the cone"], "negative_caption": ["A kid on skateboard jumps onto the cone"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:674436", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000389933.jpg", "positive_caption": ["A dog is looking at the camera sadly."], "negative_caption": ["A dog is looking past the camera sadly."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:816132", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000568213.jpg", "positive_caption": ["a young man attempting to throw a Frisbee past a defender"], "negative_caption": ["A young man attempting to throw a frisbee to a defender"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:706528", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000496409.jpg", "positive_caption": ["A skier slaloms down a snowy hill in low visibility"], "negative_caption": ["A skier slaloms up a snowy hill in low visibility"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:579213", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000111609.jpg", "positive_caption": ["A man is sleeping with the covers pulled up high."], "negative_caption": ["A man is sleeping with the covers pulled down high."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:597024", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000057027.jpg", "positive_caption": ["A baby elephant walks with an older elephant"], "negative_caption": ["A baby elephant walks past an older elephant"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:657389", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000058539.jpg", "positive_caption": ["A man in a red hat, suit, and blue striped tie walks past two other men on a street."], "negative_caption": ["A man in a red hat, suit, and blue striped tie walks toward two other men on a street."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:657362", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000297147.jpg", "positive_caption": ["A silver and black sports motorcycle parked near a building."], "negative_caption": ["A silver and black sports motorcycle parked in a building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:648733", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000451150.jpg", "positive_caption": ["Half a dozen donuts are sitting in a box."], "negative_caption": ["Half a dozen donuts are sitting near a box."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:356482", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000107851.jpg", "positive_caption": ["A group of people taking a ride on a group of elephants."], "negative_caption": ["A group of people taking a ride around a group of elephants."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:285011", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000136334.jpg", "positive_caption": ["A person skiing down a hill maneuvers around a flag."], "negative_caption": ["A person skiing down a hill maneuvers over a flag."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:83768", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000483999.jpg", "positive_caption": ["A group of people gathered at a table in a restaurant."], "negative_caption": ["A group of people gathered at a table near a restaurant."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:262782", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000376307.jpg", "positive_caption": ["The two women sit near the blender next to a table covered in fruit."], "negative_caption": ["The two women sit in the blender next to a table covered in fruit."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:813518", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000241677.jpg", "positive_caption": ["a bunch of people on camels walk up some stairs"], "negative_caption": ["A bunch of people on camels walk down some stairs"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:758437", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000326542.jpg", "positive_caption": ["a man riding skis down a snow covered slope."], "negative_caption": ["A man riding skis up a snow covered slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:697786", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000241297.jpg", "positive_caption": ["A train with a gold front is going down the tracks."], "negative_caption": ["A train with a gold front is going up the tracks."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:538456", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000272364.jpg", "positive_caption": ["Four tall giraffe are looking up to eat from a feeder."], "negative_caption": ["Four tall giraffe are looking down to eat from a feeder."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:658773", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000403817.jpg", "positive_caption": ["The grey and white cat stares up near a laptop."], "negative_caption": ["The grey and white cat stares down near a laptop."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:398644", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000290081.jpg", "positive_caption": ["A group of oranges are sitting in the bowl"], "negative_caption": ["A group of oranges are sitting near the bowl"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:737700", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000036494.jpg", "positive_caption": ["a bunch of people gathered inside of a building"], "negative_caption": ["A bunch of people gathered out of a building"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:641154", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000242678.jpg", "positive_caption": ["The horse and rider are jumping over the yellow structure."], "negative_caption": ["The horse and rider are jumping through the yellow structure."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:795008", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000172649.jpg", "positive_caption": ["a kid rides a skate board up a wall"], "negative_caption": ["A kid rides a skate board down a wall"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:543721", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000190841.jpg", "positive_caption": ["A man on a skateboard jumps over a ramp."], "negative_caption": ["A man on a skateboard jumps down a ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:462572", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000117645.jpg", "positive_caption": ["A man on skis is going down a slope."], "negative_caption": ["A man on skis is going up a slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:356669", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000331604.jpg", "positive_caption": ["A man is flying up on his surf board over an ocean."], "negative_caption": ["A man is flying back on his surf board over an ocean."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:228180", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000541291.jpg", "positive_caption": ["The old, dilapidated  bathroom has fallen into disrepair."], "negative_caption": ["The old, dilapidated bathroom has fallen from disrepair."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:804991", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000568213.jpg", "positive_caption": ["The player tries to block the other player from throwing a Frisbee."], "negative_caption": ["The player tries to block the other player into throwing a frisbee."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:709783", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000338986.jpg", "positive_caption": ["A blue train is coming down the tracks"], "negative_caption": ["A blue train is coming up the tracks"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:169159", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000013546.jpg", "positive_caption": ["A young man riding a skateboard on a stone wall."], "negative_caption": ["A young man riding a skateboard over a stone wall."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:108422", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000419408.jpg", "positive_caption": ["The skateboarder is jumping over the railing in a park."], "negative_caption": ["The skateboarder is jumping to the railing in a park."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:686763", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000280930.jpg", "positive_caption": ["there is a young girl putting food in to a oven"], "negative_caption": ["There is a young girl putting food out to a oven"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:689925", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000252294.jpg", "positive_caption": ["A pair of people lean out from behind curtains and smile."], "negative_caption": ["A pair of people lean in from behind curtains and smile."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:740197", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000290248.jpg", "positive_caption": ["People walk down a crowded street at a festival"], "negative_caption": ["People walk up a crowded street at a festival"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:647696", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000411530.jpg", "positive_caption": ["Skiers wait to take a lift up a snowy hill."], "negative_caption": ["Skiers wait to take a lift down a snowy hill."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:156633", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000007278.jpg", "positive_caption": ["there is a male surfer that is riding in the wave"], "negative_caption": ["There is a male surfer that is riding over the wave"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:687469", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000230983.jpg", "positive_caption": ["The boy jumps with a skateboard over the garbage can."], "negative_caption": ["The boy jumps with a skateboard toward the garbage can."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:359862", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000106330.jpg", "positive_caption": ["The stuffed teddy bear is sitting near the wall."], "negative_caption": ["The stuffed teddy bear is sitting in the wall."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:157895", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000361506.jpg", "positive_caption": ["The skateboarder does an aerial stunt onto the road."], "negative_caption": ["The skateboarder does an aerial stunt over the road."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:173888", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000121586.jpg", "positive_caption": ["A cat is on the television screen in an office."], "negative_caption": ["A cat is below the television screen in an office."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:736739", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000427649.jpg", "positive_caption": ["The boat sits in the lake below the mountain."], "negative_caption": ["The boat sits in the lake on the mountain."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:128395", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000326542.jpg", "positive_caption": ["there is a male skier going down a hill"], "negative_caption": ["There is a male skier going over a hill"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:690370", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000371042.jpg", "positive_caption": ["The man playing tennis is reaching up to hit the ball."], "negative_caption": ["The man playing tennis is reaching down to hit the ball."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:827081", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000480021.jpg", "positive_caption": ["A vintage, colored drawing of people on motorcycles pulled into a gas station."], "negative_caption": ["A vintage, colored drawing of people on motorcycles pulled from a gas station."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:315428", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000098392.jpg", "positive_caption": ["A double decker bus makes its way past a tall clock tower."], "negative_caption": ["A double decker bus makes its way through a tall clock tower."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:227114", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000389532.jpg", "positive_caption": ["The man is on the edge to take a picture."], "negative_caption": ["The man is over the edge to take a picture."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:819028", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000243075.jpg", "positive_caption": ["A wet polar bear looks up at the sky in his zoo enclosure"], "negative_caption": ["A wet polar bear looks down at the sky in his zoo enclosure"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:488807", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000082696.jpg", "positive_caption": ["A bird is walking right through a dining room."], "negative_caption": ["A bird is walking right by a dining room."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:79622", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000507081.jpg", "positive_caption": ["A dark kitchen with a window letting in daylight."], "negative_caption": ["A dark kitchen with a window letting out daylight."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:273295", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000263463.jpg", "positive_caption": ["A dog sticks his head out of a car window."], "negative_caption": ["A dog sticks his head in of a car window."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:357038", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000236690.jpg", "positive_caption": ["A large white bird flies over the water."], "negative_caption": ["A large white bird flies into the water."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:145142", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000356498.jpg", "positive_caption": ["A pancake with vegetables piled up on it"], "negative_caption": ["A pancake with vegetables piled down on it"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:455470", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000359540.jpg", "positive_caption": ["A spirited game of baseball takes place behind a chain link fence."], "negative_caption": ["A spirited game of baseball takes place atop a chain link fence."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:634135", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000312340.jpg", "positive_caption": ["A black and white cat relaxes atop a bunch of leaves"], "negative_caption": ["A black and white cat relaxes behind a bunch of leaves"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:287183", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000538067.jpg", "positive_caption": ["a hilly grassy area filled with people sitting down and taking pictures"], "negative_caption": ["A hilly grassy area filled with people sitting up and taking pictures"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:691811", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000135902.jpg", "positive_caption": ["A train sits running in a modern station."], "negative_caption": ["A train sits running past a modern station."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:802606", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000540928.jpg", "positive_caption": ["A cat is walking past a chair."], "negative_caption": ["A cat is walking to a chair."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:612456", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000128112.jpg", "positive_caption": ["this is a man riding skis down a hill"], "negative_caption": ["This is a man riding skis up a hill"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:693411", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000365207.jpg", "positive_caption": ["A side mirror shows a dog sticking its head out of a car window."], "negative_caption": ["A side mirror shows a dog sticking its head in of a car window."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:268890", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000146831.jpg", "positive_caption": ["Someone riding a skateboard is going up the ramp."], "negative_caption": ["Someone riding a skateboard is going down the ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:652657", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000121506.jpg", "positive_caption": ["An umbrella on a backyard patio is upturned from the wind."], "negative_caption": ["An umbrella on a backyard patio is upturned into the wind."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:706899", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000097924.jpg", "positive_caption": ["Three people are loading a horse into a horse trailer."], "negative_caption": ["Three people are loading a horse from a horse trailer."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:742461", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000031735.jpg", "positive_caption": ["A living room with red walls and dark furniture, with light streaming in two windows."], "negative_caption": ["A living room with red walls and dark furniture, with light streaming out two windows."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:172666", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000553990.jpg", "positive_caption": ["A woman is riding a horse as it jumps over a bar."], "negative_caption": ["A woman is riding a horse as it jumps down a bar."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:679072", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000568439.jpg", "positive_caption": ["A man walking down a street past a double decker bus."], "negative_caption": ["A man walking down a street towards a double decker bus."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:780926", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000363072.jpg", "positive_caption": ["The commuter train is headed toward the tall building."], "negative_caption": ["The commuter train is headed past the tall building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:661200", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000464144.jpg", "positive_caption": ["The man is skiing down the hill with his goggles up."], "negative_caption": ["The man is skiing up the hill with his goggles up."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:570905", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000287649.jpg", "positive_caption": ["A kitty cat looks up from a desk, near a keyboard."], "negative_caption": ["A kitty cat looks down from a desk, near a keyboard."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:593871", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000436551.jpg", "positive_caption": ["two black birds are swimming  in some water"], "negative_caption": ["Two black birds are swimming from some water"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:51484", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000084752.jpg", "positive_caption": ["The jet fighter sits on a pedestal across the street from a building."], "negative_caption": ["The jet fighter sits on a pedestal across the street in a building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:215309", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000010995.jpg", "positive_caption": ["A small room with a bed and window letting in light."], "negative_caption": ["A small room with a bed and window letting out light."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:606939", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000442661.jpg", "positive_caption": ["A plush giraffe is posed to look out a window."], "negative_caption": ["A plush giraffe is posed to look into a window."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:553316", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000417911.jpg", "positive_caption": ["A man is drenched by the spray from the crest of a wave as he attempts to stand up on his surfboard."], "negative_caption": ["A man is drenched by the spray from the crest of a wave as he attempts to stand down on his surfboard."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:56119", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000353970.jpg", "positive_caption": ["This cat is looking up from a chair."], "negative_caption": ["This cat is looking down from a chair."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:707687", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000117645.jpg", "positive_caption": ["A man riding a snowboard down a snow covered slope."], "negative_caption": ["A man riding a snowboard up a snow covered slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:349967", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000007888.jpg", "positive_caption": ["We are looking up at a large square clock on a pole."], "negative_caption": ["We are looking down at a large square clock on a pole."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:518375", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000086220.jpg", "positive_caption": ["A tram and a car make their way through town."], "negative_caption": ["A tram and a car make their way from town."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:61306", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000186422.jpg", "positive_caption": ["a brown bear is walking away from a river"], "negative_caption": ["A brown bear is walking away through a river"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:582802", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000260106.jpg", "positive_caption": ["A man on a horse during  a race jumps over a hurdle"], "negative_caption": ["A man on a horse during a race jumps down a hurdle"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:417781", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000314251.jpg", "positive_caption": ["A parade of motorcycles is going through a group of tall trees."], "negative_caption": ["A parade of motorcycles is going over a group of tall trees."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:1879", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000461751.jpg", "positive_caption": ["A man sitting on a motorcycle smoking a cigarette."], "negative_caption": ["A man sitting alongside a motorcycle smoking a cigarette."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:668102", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000278848.jpg", "positive_caption": ["People are standing in the rain alongside a bus."], "negative_caption": ["People are standing in the rain on a bus."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:583164", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000302165.jpg", "positive_caption": ["The cows are laying in their stalls in the barn."], "negative_caption": ["The cows are laying in their stalls near the barn."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:185603", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000190676.jpg", "positive_caption": ["A panoramic shot of several people standing near a plane."], "negative_caption": ["A panoramic shot of several people standing in a plane."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:639733", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000476415.jpg", "positive_caption": ["A guy wearing a tie has his hands in his pockets."], "negative_caption": ["A guy wearing a tie has his hands from his pockets."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:159464", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000127092.jpg", "positive_caption": ["A historic trolley sign is across the street from a large building."], "negative_caption": ["A historic trolley sign is across the street in a large building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:614993", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000064868.jpg", "positive_caption": ["A man smiles maniacly while putting a dog into an oven."], "negative_caption": ["A man smiles maniacly while putting a dog from an oven."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:342493", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000425221.jpg", "positive_caption": ["A plane is flying away from the airport"], "negative_caption": ["A plane is flying away to the airport"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:101633", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000480985.jpg", "positive_caption": ["A motorcycle is parked inside of a building."], "negative_caption": ["A motorcycle is parked atop of a building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:374665", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000549136.jpg", "positive_caption": ["A stuffed animal sits atop a barbed wire fence."], "negative_caption": ["A stuffed animal sits inside a barbed wire fence."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:123683", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000209613.jpg", "positive_caption": ["Three look alike dogs are herding sheep into a pile."], "negative_caption": ["Three look alike dogs are herding sheep from a pile."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:261466", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000329447.jpg", "positive_caption": ["A dog runs around a herd of cows in a field."], "negative_caption": ["A dog runs into a herd of cows in a field."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:829619", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000032570.jpg", "positive_caption": ["A crashing wave is about to close in on a surfer."], "negative_caption": ["A crashing wave is about to close out on a surfer."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:251894", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000190140.jpg", "positive_caption": ["A man driving a boat with his dog looking out over the bow."], "negative_caption": ["A man driving a boat with his dog looking in over the bow."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:272659", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000395903.jpg", "positive_caption": ["A surfer walks into the waves on the shore."], "negative_caption": ["A surfer walks over the waves on the shore."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:643017", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000422670.jpg", "positive_caption": ["The little baby is reaching up with his hand."], "negative_caption": ["The little baby is reaching over with his hand."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:353069", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000384666.jpg", "positive_caption": ["There are some skiers heading down a slope"], "negative_caption": ["There are some skiers heading up a slope"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:139869", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000079837.jpg", "positive_caption": ["The boats are in the water for a peaceful night"], "negative_caption": ["The boats are out the water for a peaceful night"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:576347", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000161609.jpg", "positive_caption": ["A dog peeks out from the backpack of a man at the airport"], "negative_caption": ["A dog peeks in from the backpack of a man at the airport"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:244687", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000314709.jpg", "positive_caption": ["A man riding skis down a snow covered slope."], "negative_caption": ["A man riding skis up a snow covered slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:611744", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000464689.jpg", "positive_caption": ["these stairs are leading up to an open door"], "negative_caption": ["These stairs are leading down to an open door"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:656469", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000475064.jpg", "positive_caption": ["A person is holding up a half eaten pastry."], "negative_caption": ["A person is holding down a half eaten pastry."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:506341", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000248810.jpg", "positive_caption": ["A giraffe is looking over a metal fence."], "negative_caption": ["A giraffe is looking down a metal fence."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:675519", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000475150.jpg", "positive_caption": ["A giraffe stands near a tree in the wilderness."], "negative_caption": ["A giraffe stands in a tree in the wilderness."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:279975", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000565012.jpg", "positive_caption": ["a digitally manipulated image of cars on a highway at night in the city"], "negative_caption": ["A digitally manipulated image of cars on a highway at night near the city"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:717603", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000043435.jpg", "positive_caption": ["Two men ride surfboards through the crashing waves."], "negative_caption": ["Two men ride surfboards above the crashing waves."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:802567", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000082821.jpg", "positive_caption": ["Paddleboats are lined up and ready for tourists this morning"], "negative_caption": ["Paddleboats are lined down and ready for tourists this morning"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:526066", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000138492.jpg", "positive_caption": ["A dog is reaching up to grab a Frisbee in his mouth."], "negative_caption": ["A dog is reaching back to grab a frisbee in his mouth."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:288065", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000007818.jpg", "positive_caption": ["Stemware is set face down on an elegantly set table."], "negative_caption": ["Stemware is set face up on an elegantly set table."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:162321", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000198510.jpg", "positive_caption": ["A man carrying a bag walking down the train tracks."], "negative_caption": ["A man carrying a bag walking up the train tracks."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:615228", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000273551.jpg", "positive_caption": ["a couple of motorcycles are lined up on the road"], "negative_caption": ["A couple of motorcycles are lined down on the road"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:810319", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000431727.jpg", "positive_caption": ["A pair of bears climb up in a tree."], "negative_caption": ["A pair of bears climb down in a tree."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:148529", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000378244.jpg", "positive_caption": ["A person skis through some trees down a hill"], "negative_caption": ["A person skis over some trees down a hill"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:425529", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000360960.jpg", "positive_caption": ["A person is holding up a large colorful umbrella"], "negative_caption": ["A person is holding down a large colorful umbrella"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:487760", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000161781.jpg", "positive_caption": ["A person riding skis down a hill on a race course."], "negative_caption": ["A person riding skis up a hill on a race course."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:512916", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000005037.jpg", "positive_caption": ["a bus stops to pick up some passengers"], "negative_caption": ["A bus stops to pick down some passengers"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:820166", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000063154.jpg", "positive_caption": ["A surfer paddles over a wave in clear blue water."], "negative_caption": ["A surfer paddles around a wave in clear blue water."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:60307", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000259625.jpg", "positive_caption": ["An elephant walks around a fenced in area."], "negative_caption": ["An elephant walks around a fenced out area."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:477012", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000267933.jpg", "positive_caption": ["A line of horses are walking around a river."], "negative_caption": ["A line of horses are walking over a river."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:238411", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000275727.jpg", "positive_caption": ["A train is moving along the tracks past a traffic signal."], "negative_caption": ["A train is moving along the tracks to a traffic signal."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:625297", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000168619.jpg", "positive_caption": ["A narrow pathway leads to a residential area."], "negative_caption": ["A narrow pathway leads past a residential area."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:711968", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000493019.jpg", "positive_caption": ["A group of zebras are bending down and eating a box full of grass."], "negative_caption": ["A group of zebras are bending up and eating a box full of grass."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:406205", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000567432.jpg", "positive_caption": ["A red airplane jet flies over power lines in an empty sky."], "negative_caption": ["A red airplane jet flies through power lines in an empty sky."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:458937", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000575187.jpg", "positive_caption": ["A man feeding a giraffe through a metal fence"], "negative_caption": ["A man feeding a giraffe over a metal fence"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:333056", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000372819.jpg", "positive_caption": ["Four smaller dogs are running away from the women on the bench."], "negative_caption": ["Four smaller dogs are running away toward the women on the bench."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:453208", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000225670.jpg", "positive_caption": ["a dog is jumping in the air toward a disk"], "negative_caption": ["A dog is jumping in the air from a disk"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:583363", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000570448.jpg", "positive_caption": ["A man stands on a fishing boat as the tide rolls in from the shore on a desolate beach."], "negative_caption": ["A man stands on a fishing boat as the tide rolls out from the shore on a desolate beach."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:160517", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000126110.jpg", "positive_caption": ["A dog is looking out the window of a yellow truck."], "negative_caption": ["A dog is looking in the window of a yellow truck."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:80725", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000454798.jpg", "positive_caption": ["A young boy rides a horse up a small ramp."], "negative_caption": ["A young boy rides a horse down a small ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:692293", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000161781.jpg", "positive_caption": ["A woman is skiing down a hill with safety netting."], "negative_caption": ["A woman is skiing up a hill with safety netting."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:514767", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000558073.jpg", "positive_caption": ["An adult cat is sitting inside of a bathtub."], "negative_caption": ["An adult cat is sitting atop of a bathtub."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:47929", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000322968.jpg", "positive_caption": ["A clock is situated atop a colorful tower."], "negative_caption": ["A clock is situated inside a colorful tower."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:583538", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000396863.jpg", "positive_caption": ["A young girl rides a pony by a river on a sunny day"], "negative_caption": ["A young girl rides a pony through a river on a sunny day"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:93602", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000099242.jpg", "positive_caption": ["An older man is skiing down a snowy mountain."], "negative_caption": ["An older man is skiing up a snowy mountain."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:16047", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000428111.jpg", "positive_caption": ["A man riding a skateboard up the side of a ramp."], "negative_caption": ["A man riding a skateboard down the side of a ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:697001", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000463618.jpg", "positive_caption": ["A woman sits by a bird cage holding a baby"], "negative_caption": ["A woman sits in a bird cage holding a baby"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:358388", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000127660.jpg", "positive_caption": ["A girl with a black eye and pig tails sits in a suitcase."], "negative_caption": ["A girl with a black eye and pig tails sits by a suitcase."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:441073", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000184611.jpg", "positive_caption": ["People use rickshaws to transport luggage down the street."], "negative_caption": ["People use rickshaws to transport luggage up the street."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:89951", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000301563.jpg", "positive_caption": ["The man is skiing down the snowy slopes."], "negative_caption": ["The man is skiing up the snowy slopes."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:790997", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000092839.jpg", "positive_caption": ["The polar bear has his chin up as he lies on his chest"], "negative_caption": ["The polar bear has his chin down as he lies on his chest"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:301280", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000140583.jpg", "positive_caption": ["A herd of sheep with two sherds moving down a road in the mountains."], "negative_caption": ["A herd of sheep with two sherds moving up a road in the mountains."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:385394", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000338986.jpg", "positive_caption": ["A train pulls up along some buildings."], "negative_caption": ["A train pulls down along some buildings."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:158563", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000546659.jpg", "positive_caption": ["A locomotive train carrying carts down a track."], "negative_caption": ["A locomotive train carrying carts up a track."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:826602", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000565469.jpg", "positive_caption": ["A tall building with a clock tower that is lit up at the top."], "negative_caption": ["A tall building with a clock tower that is lit down at the top."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:343786", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000287545.jpg", "positive_caption": ["Two giraffes look over a railing blockade."], "negative_caption": ["Two giraffes look through a railing blockade."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:426425", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000491470.jpg", "positive_caption": ["The road in the city is quiet and empty."], "negative_caption": ["The road past the city is quiet and empty."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:494160", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000333745.jpg", "positive_caption": ["A woman with an umbrella is walking past a bus."], "negative_caption": ["A woman with an umbrella is walking toward a bus."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:579770", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000101787.jpg", "positive_caption": ["An airplane flies high above in the sky with telephone lines in the picture as well."], "negative_caption": ["An airplane flies high down in the sky with telephone lines in the picture as well."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:477090", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000303863.jpg", "positive_caption": ["A train is traveling down the rail road tracks."], "negative_caption": ["A train is traveling above the rail road tracks."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:468894", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000361586.jpg", "positive_caption": ["Some people are checking in at the ticket counter somewhere in Asia."], "negative_caption": ["Some people are checking out at the ticket counter somewhere in asia."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:340689", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000199977.jpg", "positive_caption": ["a plane flies through the air with fumes coming out the back"], "negative_caption": ["A plane flies through the air with fumes coming in the back"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:362797", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000393469.jpg", "positive_caption": ["A man knees down on the side of a snow filled mountainside."], "negative_caption": ["A man knees up on the side of a snow filled mountainside."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:14694", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000359833.jpg", "positive_caption": ["a kid is reaching up to some apples"], "negative_caption": ["A kid is reaching down to some apples"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:577633", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000350405.jpg", "positive_caption": ["A man riding a snowboard down a ski slope."], "negative_caption": ["A man riding a snowboard up a ski slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:428763", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000485802.jpg", "positive_caption": ["A plane flying straight up and high in the sky leaves a tail of smoke."], "negative_caption": ["A plane flying straight down and high in the sky leaves a tail of smoke."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:61341", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000389684.jpg", "positive_caption": ["a man walks down a sidewalk as a vehicle passes"], "negative_caption": ["A man walks up a sidewalk as a vehicle passes"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:393045", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000168883.jpg", "positive_caption": ["Two people and a child are dressed up in costumes."], "negative_caption": ["Two people and a child are dressed down in costumes."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:52813", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000230983.jpg", "positive_caption": ["A person is doing a trick over a trash can."], "negative_caption": ["A person is doing a trick inside a trash can."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:354081", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000220310.jpg", "positive_caption": ["A teddy bear with a giant heart sits inside a green bin."], "negative_caption": ["A teddy bear with a giant heart sits over a green bin."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:508269", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000396568.jpg", "positive_caption": ["An orange train is going down the tracks."], "negative_caption": ["An orange train is going up the tracks."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:384939", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000506933.jpg", "positive_caption": ["A man with glasses is holding up an iPhone."], "negative_caption": ["A man with glasses is holding down an iphone."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:721199", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000301563.jpg", "positive_caption": ["A man riding skis down a snow covered slope."], "negative_caption": ["A man riding skis up a snow covered slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:784868", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000491008.jpg", "positive_caption": ["A waitress and a man are holding up a large pizza."], "negative_caption": ["A waitress and a man are holding down a large pizza."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:279588", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000087470.jpg", "positive_caption": ["Many cows travel down the side of a street"], "negative_caption": ["Many cows travel up the side of a street"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:619110", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000321790.jpg", "positive_caption": ["A young man holds up a tennis racket."], "negative_caption": ["A young man holds down a tennis racket."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:811162", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000245915.jpg", "positive_caption": ["A herd of elephants are walking through a river."], "negative_caption": ["A herd of elephants are walking over a river."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:204408", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000492968.jpg", "positive_caption": ["This image is of a man snowboarding down a hill."], "negative_caption": ["This image is of a man snowboarding up a hill."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:226504", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000292415.jpg", "positive_caption": ["A man riding a skateboard up the side of a ramp."], "negative_caption": ["A man riding a skateboard down the side of a ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:199189", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000112997.jpg", "positive_caption": ["a person is holding up an old cellphone"], "negative_caption": ["A person is holding down an old cellphone"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:576887", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000038210.jpg", "positive_caption": ["a skier is prepared to go down a mountain."], "negative_caption": ["A skier is prepared to go up a mountain."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:658263", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000193743.jpg", "positive_caption": ["A man standing on a tennis court waves to someone."], "negative_caption": ["A man standing on a tennis court waves past someone."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:112318", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000491725.jpg", "positive_caption": ["Small sailboats are lit up on the water."], "negative_caption": ["Small sailboats are lit down on the water."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:605108", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000177861.jpg", "positive_caption": ["A group of people walking down a wet rain soaked sidewalk."], "negative_caption": ["A group of people walking up a wet rain soaked sidewalk."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:552826", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000439593.jpg", "positive_caption": ["A passenger train pulls into a train station."], "negative_caption": ["A passenger train pulls past a train station."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:27454", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000314709.jpg", "positive_caption": ["A guy is having fun skiing down the slope of the hill."], "negative_caption": ["A guy is having fun skiing up the slope of the hill."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:613580", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000544444.jpg", "positive_caption": ["A person skis down a snowy hill."], "negative_caption": ["A person skis up a snowy hill."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:272448", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000379332.jpg", "positive_caption": ["A tennis player is looking up to the sky."], "negative_caption": ["A tennis player is looking down to the sky."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:356762", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000491216.jpg", "positive_caption": ["A cat is walking in a kitchen that has cookware hanging on the wall."], "negative_caption": ["A cat is walking past a kitchen that has cookware hanging on the wall."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:616409", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000396863.jpg", "positive_caption": ["A girl on a horse rides past a lake."], "negative_caption": ["A girl on a horse rides into a lake."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:87758", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000329827.jpg", "positive_caption": ["Blurry photograph of a woman skiing down a slope"], "negative_caption": ["Blurry photograph of a woman skiing up a slope"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:625065", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000001296.jpg", "positive_caption": ["A woman holds up her phone in front of her face."], "negative_caption": ["A woman holds down her phone in front of her face."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:374270", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000520301.jpg", "positive_caption": ["A brown medium sized dog stares out of a window."], "negative_caption": ["A brown medium sized dog stares in of a window."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:743899", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000322610.jpg", "positive_caption": ["A woman walking past a shop filled with merchandise."], "negative_caption": ["A woman walking into a shop filled with merchandise."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:36359", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000172977.jpg", "positive_caption": ["The medium sized zebra is looking into the camera."], "negative_caption": ["The medium sized zebra is looking past the camera."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:513650", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000497599.jpg", "positive_caption": ["A man with a beard and mustache thoughtfully stares into a computer screen at some sort of a meeting."], "negative_caption": ["A man with a beard and mustache thoughtfully stares past a computer screen at some sort of a meeting."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:91757", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000076625.jpg", "positive_caption": ["A blue train traveling past a train station next to a lush green mountain."], "negative_caption": ["A blue train traveling into a train station next to a lush green mountain."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:291582", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000094614.jpg", "positive_caption": ["A man riding skis down the side of a snow covered ski slope."], "negative_caption": ["A man riding skis up the side of a snow covered ski slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:121305", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000491008.jpg", "positive_caption": ["A man and woman are holding up a pizza."], "negative_caption": ["A man and woman are holding down a pizza."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:279723", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000306437.jpg", "positive_caption": ["A man riding a skateboard up a flight of steps."], "negative_caption": ["A man riding a skateboard down a flight of steps."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:583878", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000187055.jpg", "positive_caption": ["A man throws tennis balls to waiting tennis players."], "negative_caption": ["A man throws tennis balls past waiting tennis players."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:212772", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000090956.jpg", "positive_caption": ["a skier in a green shirt is coming down a mountain"], "negative_caption": ["A skier in a green shirt is coming up a mountain"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:222204", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000505169.jpg", "positive_caption": ["a bath room with a stand up shower and a toilet"], "negative_caption": ["A bath room with a stand down shower and a toilet"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:468087", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000301563.jpg", "positive_caption": ["a man skiing down a hill by himself"], "negative_caption": ["A man skiing over a hill by himself"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:790481", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000525155.jpg", "positive_caption": ["A sheep is being carried up a hill."], "negative_caption": ["A sheep is being carried down a hill."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:56864", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000172935.jpg", "positive_caption": ["a person flying backwards on skis over water"], "negative_caption": ["A person flying backwards on skis through water"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:307031", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000165500.jpg", "positive_caption": ["a couple of animals walk through the grass"], "negative_caption": ["A couple of animals walk over the grass"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:776128", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000529939.jpg", "positive_caption": ["A man walking toward a line of surfboards lined up along a shop wall."], "negative_caption": ["A man walking past a line of surfboards lined up along a shop wall."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:692849", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000151516.jpg", "positive_caption": ["A brown bird with a white head flys over  a large body of water."], "negative_caption": ["A brown bird with a white head flys through a large body of water."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:8464", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000038118.jpg", "positive_caption": ["The man is skiing down the snowy hill."], "negative_caption": ["The man is skiing up the snowy hill."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:450604", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000378673.jpg", "positive_caption": ["A man riding a skateboard down the side of a ramp."], "negative_caption": ["A man riding a skateboard up the side of a ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:222702", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000398742.jpg", "positive_caption": ["A couple of men are holding up a team member"], "negative_caption": ["A couple of men are holding down a team member"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:189813", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000236690.jpg", "positive_caption": ["an image of a bird flying over the water"], "negative_caption": ["An image of a bird flying through the water"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:156695", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000534394.jpg", "positive_caption": ["The sheep follow each other over the short block wall."], "negative_caption": ["The sheep follow each other towards the short block wall."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:385433", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000509258.jpg", "positive_caption": ["A street sign shows directions to highways and towns."], "negative_caption": ["A street sign shows directions from highways and towns."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:51895", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000137294.jpg", "positive_caption": ["A gentleman is removing food from a cooker in a yard."], "negative_caption": ["A gentleman is removing food to a cooker in a yard."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:73277", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000404249.jpg", "positive_caption": ["A small boy rides a skateboard down the walkway."], "negative_caption": ["A small boy rides a skateboard up the walkway."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:396718", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000186042.jpg", "positive_caption": ["This is a painting of a cross country skier traveling up a slope at sunrise."], "negative_caption": ["This is a painting of a cross country skier traveling down a slope at sunrise."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:322490", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000032941.jpg", "positive_caption": ["A yellow oblong upside down triangular street sign stands in the middle of the street."], "negative_caption": ["A yellow oblong upside up triangular street sign stands in the middle of the street."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:300292", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000422670.jpg", "positive_caption": ["A baby is reaching up toward the camera."], "negative_caption": ["A baby is reaching down toward the camera."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:352082", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000183104.jpg", "positive_caption": ["Two giraffes stick their heads out and get their picture taken."], "negative_caption": ["Two giraffes stick their heads in and get their picture taken."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:117801", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000407960.jpg", "positive_caption": ["A small cat is looking up at a stove top."], "negative_caption": ["A small cat is looking down at a stove top."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:450540", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000184978.jpg", "positive_caption": ["A snowboarder headed down a hill in front of trees."], "negative_caption": ["A snowboarder headed up a hill in front of trees."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:468260", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000104603.jpg", "positive_caption": ["A black bear walks down a hill away from a tree."], "negative_caption": ["A black bear walks down a hill away into a tree."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:686212", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000253433.jpg", "positive_caption": ["A teddy bear dressed up in bondage gear."], "negative_caption": ["A teddy bear dressed down in bondage gear."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:577194", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000063047.jpg", "positive_caption": ["A man carries a bag of food and a drink away from a roadside eatery."], "negative_caption": ["A man carries a bag of food and a drink away to a roadside eatery."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:804464", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000241677.jpg", "positive_caption": ["A herd of animals walking up some steps towards a bridge crossing a river."], "negative_caption": ["A herd of animals walking up some steps from a bridge crossing a river."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:749983", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000080273.jpg", "positive_caption": ["A man snowboards down a snowy hill."], "negative_caption": ["A man snowboards up a snowy hill."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:235754", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000553731.jpg", "positive_caption": ["A man dressed up as a clown is holding a cellphone to his ear."], "negative_caption": ["A man dressed down as a clown is holding a cellphone to his ear."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:770075", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000009448.jpg", "positive_caption": ["A little girl holds up a big blue umbrella."], "negative_caption": ["A little girl holds down a big blue umbrella."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:802608", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000005529.jpg", "positive_caption": ["A person on skis is skiing down a snowy hill."], "negative_caption": ["A person on skis is skiing up a snowy hill."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:181870", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000480842.jpg", "positive_caption": ["Two giraffes are peering up above some bushes."], "negative_caption": ["Two giraffes are peering down above some bushes."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:223966", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000377635.jpg", "positive_caption": ["A man riding a skateboard up the side of a ramp."], "negative_caption": ["A man riding a skateboard down the side of a ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:381048", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000284296.jpg", "positive_caption": ["three giraffes banding down to drink water with trees in the background"], "negative_caption": ["Three giraffes banding up to drink water with trees in the background"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:278990", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000261732.jpg", "positive_caption": ["a tennis player jumps up to hit a ball on a tennis court"], "negative_caption": ["A tennis player jumps down to hit a ball on a tennis court"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:475084", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000500257.jpg", "positive_caption": ["People lined up at a ticket check in area with luggage."], "negative_caption": ["People lined up at a ticket check out area with luggage."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:110584", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000484893.jpg", "positive_caption": ["A couple of kids petting sheep inside of a corral"], "negative_caption": ["A couple of kids petting sheep out of a corral"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:222164", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000343937.jpg", "positive_caption": ["A girl glides down a snowy hill on a snowboard."], "negative_caption": ["A girl glides up a snowy hill on a snowboard."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:344632", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000506933.jpg", "positive_caption": ["a man in glasses is holding up a cellphone"], "negative_caption": ["A man in glasses is holding down a cellphone"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:720875", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000172648.jpg", "positive_caption": ["a man reaches in the back of a truck"], "negative_caption": ["A man reaches out the back of a truck"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:526322", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000365521.jpg", "positive_caption": ["A young man riding a skateboard down a rail."], "negative_caption": ["A young man riding a skateboard over a rail."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:33205", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000257169.jpg", "positive_caption": ["A person is holding up a hair dryer in the bathroom."], "negative_caption": ["A person is holding down a hair dryer in the bathroom."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:753021", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000008211.jpg", "positive_caption": ["Two men talking to each other on a street corner"], "negative_caption": ["Two men talking over each other on a street corner"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:214678", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000229601.jpg", "positive_caption": ["there is a baseball player that has just run to the base"], "negative_caption": ["There is a baseball player that has just run past the base"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:818202", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000068628.jpg", "positive_caption": ["A skateboarder does a jump trick over stairs."], "negative_caption": ["A skateboarder does a jump trick down stairs."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:393847", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000122672.jpg", "positive_caption": ["A man is riding a surfboard through a wave."], "negative_caption": ["A man is riding a surfboard against a wave."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:451140", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000299720.jpg", "positive_caption": ["A giraffe has its head pressed against the wall."], "negative_caption": ["A giraffe has its head pressed through the wall."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:287059", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000289415.jpg", "positive_caption": ["this is a pizza that is sliced up in pieces"], "negative_caption": ["This is a pizza that is sliced down in pieces"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:696417", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000336209.jpg", "positive_caption": ["A man riding a skateboard up a wooden ramp."], "negative_caption": ["A man riding a skateboard down a wooden ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:164686", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000343937.jpg", "positive_caption": ["A girl in a white jacket is snowboarding down a slope."], "negative_caption": ["A girl in a white jacket is snowboarding up a slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:343522", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000407960.jpg", "positive_caption": ["A cat is looking up at an oven."], "negative_caption": ["A cat is looking down at an oven."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:458367", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000119445.jpg", "positive_caption": ["A baseball player swings his bat while a ball floats above his head towards the catcher and umpire."], "negative_caption": ["A baseball player swings his bat while a ball floats above his head over the catcher and umpire."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:304848", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000094157.jpg", "positive_caption": ["A large, ornate clock tower rises above another skyscraper."], "negative_caption": ["A large, ornate clock tower rises against another skyscraper."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:191230", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000544605.jpg", "positive_caption": ["A street sign is pictured against a cement wall."], "negative_caption": ["A street sign is pictured above a cement wall."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:750387", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000359781.jpg", "positive_caption": ["The giraffe is walking toward a rock on a trail."], "negative_caption": ["The giraffe is walking over a rock on a trail."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:685405", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000515577.jpg", "positive_caption": ["A man riding skis down a snow covered slope."], "negative_caption": ["A man riding skis up a snow covered slope."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:181701", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000194471.jpg", "positive_caption": ["A man riding a skateboard up the side of a ramp."], "negative_caption": ["A man riding a skateboard over the side of a ramp."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:217818", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000203639.jpg", "positive_caption": ["This girl is looking down at her shoes."], "negative_caption": ["This girl is looking up at her shoes."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:314198", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000253433.jpg", "positive_caption": ["a white stuffed bear is dressed up in some gear"], "negative_caption": ["A white stuffed bear is dressed down in some gear"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:578958", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000121744.jpg", "positive_caption": ["A tennis player looks up with his leg in the air as photographers snap photos."], "negative_caption": ["A tennis player looks down with his leg in the air as photographers snap photos."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:50382", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000184978.jpg", "positive_caption": ["there is a snowboarder coming down a very steep hill"], "negative_caption": ["There is a snowboarder coming up a very steep hill"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:465950", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000376900.jpg", "positive_caption": ["The tennis player throws the ball up to serve"], "negative_caption": ["The tennis player throws the ball down to serve"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:618293", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000096825.jpg", "positive_caption": ["The elderly man  on skis is making his way down the edge of the snow-covered road."], "negative_caption": ["The elderly man on skis is making his way up the edge of the snow - covered road."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:86396", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000424551.jpg", "positive_caption": ["a person is going up a snow covered mountain"], "negative_caption": ["A person is going across a snow covered mountain"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:526880", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000245915.jpg", "positive_caption": ["A herd of elephants is moving across a stream."], "negative_caption": ["A herd of elephants is moving up a stream."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:214872", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000464689.jpg", "positive_caption": ["Concrete stairs lead to the double doors of the house."], "negative_caption": ["Concrete stairs lead from the double doors of the house."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:657996", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000372577.jpg", "positive_caption": ["A man with a tennis racket walks from the net of a tennis court."], "negative_caption": ["A man with a tennis racket walks into the net of a tennis court."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:477468", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000163118.jpg", "positive_caption": ["Two guys leap for the Frisbee as they play their game in some sort of a gym."], "negative_caption": ["Two guys leap over the frisbee as they play their game in some sort of a gym."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:387749", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000368961.jpg", "positive_caption": ["Two mini elephants walking  toward people on a plank"], "negative_caption": ["Two mini elephants walking past people on a plank"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:69105", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000350003.jpg", "positive_caption": ["A firetruck is near a brown building off a side street that veers from a main road."], "negative_caption": ["A firetruck is near a brown building off a side street that veers into a main road."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:107975", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000289586.jpg", "positive_caption": ["A giraffe points its head towards the sky"], "negative_caption": ["A giraffe points its head from the sky"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:144921", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000217400.jpg", "positive_caption": ["A train is pulling into a subway stop."], "negative_caption": ["A train is pulling past a subway stop."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:217337", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000094614.jpg", "positive_caption": ["A skier skis down a hill past a sparse evergreen."], "negative_caption": ["A skier skis down a hill into a sparse evergreen."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:135993", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000025228.jpg", "positive_caption": ["A woman looks to her right while straddling a surfboard in the ocean."], "negative_caption": ["A woman looks past her right while straddling a surfboard in the ocean."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:415105", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000177065.jpg", "positive_caption": ["A bunch of people are looking over a tennis volley net while a young boy wearing glasses is bouncing a tennis ball"], "negative_caption": ["A bunch of people are looking towards a tennis volley net while a young boy wearing glasses is bouncing a tennis ball"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:617088", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000166918.jpg", "positive_caption": ["people sitting around a long table talking to each other"], "negative_caption": ["People sitting around a long table talking over each other"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:242501", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000197388.jpg", "positive_caption": ["Four men ski down a snowy cliff in team clothing."], "negative_caption": ["Four men ski over a snowy cliff in team clothing."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:44815", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000389316.jpg", "positive_caption": ["Two elephants are standing inside of an enclosure"], "negative_caption": ["Two elephants are standing out of an enclosure"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:43761", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000464476.jpg", "positive_caption": ["A man is seen walking out of a building."], "negative_caption": ["A man is seen walking inside of a building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:613206", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000515077.jpg", "positive_caption": ["A woman is walking towards a screen that is playing a movie."], "negative_caption": ["A woman is walking past a screen that is playing a movie."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:406623", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000001584.jpg", "positive_caption": ["The red, double decker bus is driving past other buses."], "negative_caption": ["The red, double decker bus is driving towards other buses."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:732292", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000579818.jpg", "positive_caption": ["The old fashioned train is going over the bridge."], "negative_caption": ["The old fashioned train is going down the bridge."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:574768", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000180383.jpg", "positive_caption": ["A television is mounted inside of a cow figurine."], "negative_caption": ["A television is mounted out of a cow figurine."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:640753", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000308531.jpg", "positive_caption": ["a pink clock tower rises above a tree line"], "negative_caption": ["A pink clock tower rises through a tree line"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:432241", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000407083.jpg", "positive_caption": ["A small dog is looking out a car window."], "negative_caption": ["A small dog is looking into a car window."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:156885", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000423123.jpg", "positive_caption": ["two people bent over to look into a little fridge"], "negative_caption": ["Two people bent over to look out a little fridge"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:508075", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000266400.jpg", "positive_caption": ["A line of motorcycles backed in and parked in a line at the edge of a sidewalk."], "negative_caption": ["A line of motorcycles backed out and parked in a line at the edge of a sidewalk."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:370063", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000107087.jpg", "positive_caption": ["A black cat looks out from the inside of a car."], "negative_caption": ["A black cat looks in from the inside of a car."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:156546", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000171757.jpg", "positive_caption": ["A group of people standing inside of a living room."], "negative_caption": ["A group of people standing out of a living room."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:807641", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000484893.jpg", "positive_caption": ["Children reach over a short barrier to pet small sheep."], "negative_caption": ["Children reach down a short barrier to pet small sheep."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:249434", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000469828.jpg", "positive_caption": ["The skier is quickly racing past the yellow flag."], "negative_caption": ["The skier is quickly racing to the yellow flag."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:736627", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000285894.jpg", "positive_caption": ["A giraffe has come to a fence line to greet visitors."], "negative_caption": ["A giraffe has come past a fence line to greet visitors."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:160532", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000440508.jpg", "positive_caption": ["A long orange train is going between trees."], "negative_caption": ["A long orange train is going over trees."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:356408", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000143068.jpg", "positive_caption": ["A kite flies over flags posted on a windy beach."], "negative_caption": ["A kite flies between flags posted on a windy beach."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:506484", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000142238.jpg", "positive_caption": ["Two football teams lift some players into the air."], "negative_caption": ["Two football teams lift some players from the air."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:213605", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000366711.jpg", "positive_caption": ["A man is squeezing orange juice from a pile of oranges."], "negative_caption": ["A man is squeezing orange juice into a pile of oranges."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:455026", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000466986.jpg", "positive_caption": ["a man is standing inside of a food truck"], "negative_caption": ["A man is standing out of a food truck"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:617461", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000229858.jpg", "positive_caption": ["An adult and baby moose step out of a busy thicket in the wild."], "negative_caption": ["An adult and baby moose step inside of a busy thicket in the wild."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:185919", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000154718.jpg", "positive_caption": ["A man is looking into a disgusting toilet"], "negative_caption": ["A man is looking out a disgusting toilet"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:469945", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000060090.jpg", "positive_caption": ["A yellow train pulling into the train station"], "negative_caption": ["A yellow train pulling from the train station"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:105226", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000250901.jpg", "positive_caption": ["A group of people getting their food from a bag."], "negative_caption": ["A group of people getting their food into a bag."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:610673", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000132622.jpg", "positive_caption": ["a big grizzly bear looks toward the camersa"], "negative_caption": ["A big grizzly bear looks over the camersa"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:161549", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000572462.jpg", "positive_caption": ["A white train traveling through a train station."], "negative_caption": ["A white train traveling past a train station."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:508090", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000301061.jpg", "positive_caption": ["A person is moving green hay towards an elephant that is inside the back of a white truck."], "negative_caption": ["A person is moving green hay past an elephant that is inside the back of a white truck."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:85015", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000471023.jpg", "positive_caption": ["a vehicle is flying past a group of people"], "negative_caption": ["A vehicle is flying towards a group of people"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:646146", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000458223.jpg", "positive_caption": ["A man with a bike walks towards a red lighthouse."], "negative_caption": ["A man with a bike walks past a red lighthouse."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:172098", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000565778.jpg", "positive_caption": ["A blue commuter train traveling towards a train tunnel."], "negative_caption": ["A blue commuter train traveling over a train tunnel."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:96433", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000184400.jpg", "positive_caption": ["A train rides on a bridge past a building."], "negative_caption": ["A train rides on a bridge through a building."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:369519", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000578093.jpg", "positive_caption": ["A train is moving through a train station."], "negative_caption": ["A train is moving past a train station."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:428411", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000159684.jpg", "positive_caption": ["This is a picture of a train coming into the station."], "negative_caption": ["This is a picture of a train coming by the station."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:454559", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000213605.jpg", "positive_caption": ["Van drives by a bus sitting at the curb"], "negative_caption": ["Van drives into a bus sitting at the curb"], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:355517", "linguistic_phenomena": "relations", "original_split": "val"}
{"image_file_name": "coco2017/000000138979.jpg", "positive_caption": ["An SUV is driving past a city bus that is letting passengers on."], "negative_caption": ["An suv is driving to a city bus that is letting passengers on."], "original_file_name": "relations", "dataset": "coco_2017", "key": "relations:coco_2017:460969", "linguistic_phenomena": "relations", "original_split": "val"}