index int64 1 3M | question stringclasses 382
values | hint stringclasses 98
values | A stringlengths 1 460 | B stringlengths 1 460 | C stringlengths 1 460 | D stringlengths 1 460 | answer stringclasses 4
values | category stringclasses 20
values | image imagewidth (px) 55 512 | source stringclasses 569
values | l2-category stringclasses 6
values | comment stringclasses 180
values | split stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3,000,918 | Which of the following statements match the image? | nan | A blue pentagon is to the right of a gray pentagon. | A blue square is to the left of a blue pentagon. | A blue pentagon is to the left of a gray shape. | A triangle is to the left of a pentagon. | A | attribute_comparison | shapeworld | finegrained_perception (cross-instance) | world-49.png | dev | |
3,000,923 | Which of the following statements match the image? | nan | A red ellipse is above a green pentagon. | A yellow shape is below a red pentagon. | A pentagon is below a pentagon. | A green pentagon is above a red shape. | C | attribute_comparison | shapeworld | finegrained_perception (cross-instance) | world-66.png | dev | |
3,000,924 | Which of the following statements match the image? | nan | A blue semicircle is above a green shape. | A green ellipse is below a yellow rectangle. | A green ellipse is above a yellow rectangle. | A rectangle is below a green ellipse. | B | attribute_comparison | shapeworld | finegrained_perception (cross-instance) | world-68.png | dev | |
3,000,926 | Which of the following statements match the image? | nan | A cyan square is to the left of a gray circle. | A cyan ellipse is to the right of a gray circle. | A cyan circle is to the right of a circle. | A gray circle is to the left of a cyan shape. | D | attribute_comparison | shapeworld | finegrained_perception (cross-instance) | world-71.png | dev | |
3,000,927 | Which of the following statements match the image? | nan | A cross is above a cyan shape. | A rectangle is above a cyan shape. | A cyan rectangle is below a red shape. | A yellow triangle is below a red rectangle. | B | attribute_comparison | shapeworld | finegrained_perception (cross-instance) | world-74.png | dev | |
3,000,928 | What's the function of the demonstrated object? | nan | Providing food and drinks. | Ensuring safety | Maintaining the aircrafts | Transportation of people and cargo. | D | function_reasoning | COCO train2014 | attribute_reasoning | 1.png | dev | |
3,000,930 | What's the function of the demonstrated object? | nan | supply water for suppressing fire. | Maintaining the aircrafts | Offering a variety of drink | Transportation of people and cargo. | A | function_reasoning | COCO train2014 | attribute_reasoning | 3.png | dev | |
3,000,931 | What's the function of the demonstrated object? | nan | supply water for suppressing fire | Transportation of people and cargo | warning and guiding drivers | Offering a variety of drink | C | function_reasoning | COCO train2014 | attribute_reasoning | 4.png | dev | |
3,000,932 | What's the function of the demonstrated object? | nan | supply water for suppressing fire | Transportation of people and cargo | Offering a variety of drink | It can be easily transported and used in temporary spaces | D | function_reasoning | COCO train2014 | attribute_reasoning | 5.png | dev | |
3,000,933 | What's the function of the demonstrated object? | nan | bind papers together | hitting things | tighten or loosen screws | entertainment and scientific research | D | function_reasoning | COCO train2014 | attribute_reasoning | 6.png | dev | |
3,000,935 | What's the function of the demonstrated object? | nan | Play football | Play tennis | Play basketball | running | A | function_reasoning | COCO train2014 | attribute_reasoning | 8.png | dev | |
3,000,936 | What's the function of the demonstrated object? | nan | project images or videos onto a larger surface | watch TV shows | display digital photos in a slideshow format. | display information in pictorial or textual form | D | function_reasoning | COCO train2014 | attribute_reasoning | 9.png | dev | |
3,000,938 | What's the function of the demonstrated object? | nan | tool used for cleaning the toilet bowl | It is usually used to hold food | It is usually used to hold drinks | a sanitary facility used for excretion | D | function_reasoning | COCO train2014 | attribute_reasoning | 11.png | dev | |
3,000,939 | What's the function of the demonstrated object? | nan | a sanitary facility used for excretion | used as decorations. | watch TV shows | increase passenger capacity and reduce traffic congestion | D | function_reasoning | COCO train2014 | attribute_reasoning | 12.png | dev | |
3,000,941 | What's the function of the demonstrated object? | nan | sleep | a sanitary facility used for excretion | Play basketball | prepare food and cook meals | A | function_reasoning | COCO train2014 | attribute_reasoning | 14.png | dev | |
3,000,943 | What's the function of the demonstrated object? | nan | supply water for suppressing fire | Transportation of people and cargo | warning and guiding drivers | Offering a variety of drink | C | function_reasoning | COCO train2014 | attribute_reasoning | 16.png | dev | |
3,000,944 | What's the function of the demonstrated object? | nan | Offering a variety of food | Transportation of people and cargo. | Offering a variety of drink | Providing entertainment such as movies and music | B | function_reasoning | COCO train2014 | attribute_reasoning | 17.png | dev | |
3,000,946 | What's the function of the demonstrated object? | nan | Offering a variety of food | Transportation of people and cargo. | Offering a variety of drink | Providing entertainment such as movies and music | B | function_reasoning | COCO train2014 | attribute_reasoning | 19.png | dev | |
3,000,947 | What's the function of the demonstrated object? | nan | used as decorations | touchscreens instead of a physical keyboard | control the cursor on a computer screen and input text | supply water | C | function_reasoning | COCO train2014 | attribute_reasoning | 20.png | dev | |
3,000,950 | Which is the main topic of the image | nan | Tea and dessert | Coffee and salad | Juice and dessert | Coffee and dessert | D | image_topic | COCO train2014 | coarse_perception | 4.png | dev | |
3,000,951 | Which is the main topic of the image | nan | A train driving on the road | Two buses driving on the road | A car driving on the road | A bus driving on the road | D | image_topic | COCO train2014 | coarse_perception | 5.png | dev | |
3,000,952 | Which is the main topic of the image | nan | A little girl brushing her teeth naked | A little boy taking a bath naked | A little boy brushing his teeth naked | A little boy brushing his teeth with clothes on | C | image_topic | COCO train2014 | coarse_perception | 6.png | dev | |
3,000,958 | Which is the main topic of the image | nan | A goat is eating leaves | A cow is eating grass | A sheep is eating flowers | A horse is eating hay | B | image_topic | COCO train2014 | coarse_perception | 12.png | dev | |
3,000,959 | Which is the main topic of the image | nan | A man is playing tennis | A boy is playing soccer | A girl is playing volleyball | A woman is playing tennis | A | image_topic | COCO train2014 | coarse_perception | 13.png | dev | |
3,000,960 | Which is the main topic of the image | nan | In a soccer game, the goalkeeper is holding a yellow card | In a soccer game, the goalkeeper is holding the soccer ball | In a soccer game, the goalkeeper is holding a red card | In a soccer game, the goalkeeper is holding the opponent’s jersey | B | image_topic | COCO train2014 | coarse_perception | 14.png | dev | |
3,000,961 | Which is the main topic of the image | nan | Driving buses | A driving bus | A driving car | Driving cars | A | image_topic | COCO train2014 | coarse_perception | 15.png | dev | |
3,000,962 | Which is the main topic of the image | nan | A man skiting | A man surfing | A woman skiting | A woman surfing | B | image_topic | COCO train2014 | coarse_perception | 16.png | dev | |
3,000,963 | Which is the main topic of the image | nan | A girl skiting | A man skiting | A woman skiting | A boy skiting | B | image_topic | COCO train2014 | coarse_perception | 17.png | dev | |
3,000,964 | Which is the main topic of the image | nan | A man is holding a hamburger | A man is holding a sandwich | A man is holding a pizza | A man is holding a hot dog | A | image_topic | COCO train2014 | coarse_perception | 18.png | dev | |
3,000,965 | Which is the main topic of the image | nan | A toy bear and a toy chicken | A toy bear and a toy cat | A toy bear and a toy rabbit | A toy bear and a toy dog | A | image_topic | COCO train2014 | coarse_perception | 19.png | dev | |
3,000,967 | Where is it located? | nan | Shanghai | Beijing | Nanjing | Xi'an | D | celebrity_recognition | https://img1.baidu.com/it/u=2949121113,2134614678&fm=253&fmt=auto&app=138&f=JPEG?w=500&h=546 | finegrained_perception (instance-level) | 1.png | dev | |
3,000,968 | Where is it located? | nan | Shanghai | Xi'an | Beijing | Tokyo | B | celebrity_recognition | https://img0.baidu.com/it/u=2074856582,1191410713&fm=253&fmt=auto&app=120&f=JPEG?w=1331&h=800 | finegrained_perception (instance-level) | 2.png | dev | |
3,000,969 | Where is it located? | nan | Shanghai | Beijing | Nanjing | Xi'an | D | celebrity_recognition | https://img0.baidu.com/it/u=3201893461,3488246461&fm=253&fmt=auto&app=138&f=JPEG?w=500&h=334 | finegrained_perception (instance-level) | 3.png | dev | |
3,000,970 | Where is it located? | nan | Canton | Beijing | Xi'an | Chengdu | C | celebrity_recognition | https://img1.baidu.com/it/u=406353686,381926990&fm=253&fmt=auto&app=138&f=JPEG?w=750&h=500 | finegrained_perception (instance-level) | 4.png | dev | |
3,000,971 | Where is it? | nan | Xi'an | Wuhan | Nanjing | Shanghai | A | celebrity_recognition | https://img1.baidu.com/it/u=3543021369,1113883513&fm=253&fmt=auto&app=138&f=JPEG?w=892&h=500 | finegrained_perception (instance-level) | 5.png | dev | |
3,000,973 | What is the name of this river | nan | Yangtze River | Huanghe River | Pearl River | Huangpu River | D | celebrity_recognition | https://img0.baidu.com/it/u=69631095,1079062567&fm=253&fmt=auto&app=138&f=JPEG?w=875&h=500 | finegrained_perception (instance-level) | 7.png | dev | |
3,000,974 | Where is it? | nan | London | Shanghai | Milan | Pari | B | celebrity_recognition | https://img0.baidu.com/it/u=221396920,1553768820&fm=253&fmt=auto&app=138&f=JPEG?w=620&h=364 | finegrained_perception (instance-level) | 8.png | dev | |
3,000,975 | Where is it located? | nan | Shanghai | Beijing | Nanjing | Xi'an | A | celebrity_recognition | https://img2.baidu.com/it/u=2437820198,190290422&fm=253&fmt=auto&app=138&f=JPEG?w=767&h=500 | finegrained_perception (instance-level) | 9.png | dev | |
3,000,976 | What is the name of this building? | nan | Jin Mao Tower | Burj Khalifa | Shanghai World Financial Center | Shanghai Tower | D | celebrity_recognition | https://img2.baidu.com/it/u=2280954147,4093526912&fm=253&fmt=auto&app=138&f=JPEG?w=500&h=701 | finegrained_perception (instance-level) | 10.png | dev | |
3,000,977 | What is the name of this city? | nan | London | Shanghai | Milan | Pari | D | celebrity_recognition | http://t14.baidu.com/it/u=1667352466,3373777912&fm=224&app=112&f=JPEG?w=500&h=346 | finegrained_perception (instance-level) | 11.png | dev | |
3,000,979 | Where is it? | nan | London | Shanghai | Pari | Milan | C | celebrity_recognition | https://img1.baidu.com/it/u=151765932,2068512918&fm=253&fmt=auto&app=120&f=JPEG?w=1422&h=800 | finegrained_perception (instance-level) | 13.png | dev | |
3,000,980 | Where is the name of it? | nan | Notre-Dame of Paris | Versailles | Arc de Triomphe | Louvre | D | celebrity_recognition | https://img0.baidu.com/it/u=601418823,1572285469&fm=253&fmt=auto&app=138&f=JPEG?w=500&h=310 | finegrained_perception (instance-level) | 14.png | dev | |
3,000,981 | What is the name of this river | nan | Seine River | Huanghe River | Pearl River | Huangpu River | A | celebrity_recognition | https://img1.baidu.com/it/u=527737708,1227210218&fm=253&fmt=auto&app=138&f=JPEG?w=750&h=500 | finegrained_perception (instance-level) | 15.png | dev | |
3,000,982 | Where is this? | nan | London | Shanghai | Pari | Singapore | D | celebrity_recognition | https://img1.baidu.com/it/u=1842825190,2604977287&fm=253&fmt=auto&app=138&f=JPEG?w=667&h=500 | finegrained_perception (instance-level) | 16.png | dev | |
3,000,984 | What is the name of this university | nan | Nanyang Technological University | University of Hong Kong | The Chinese University of Hong Kong | National University of Singapore | D | celebrity_recognition | https://img2.baidu.com/it/u=3652862280,2521762197&fm=253&fmt=auto&app=120&f=JPEG?w=900&h=500 | finegrained_perception (instance-level) | 18.png | dev | |
3,000,985 | Where is this? | nan | Xi'an | Singapore | Pari | Beijing | B | celebrity_recognition | https://img2.baidu.com/it/u=2479213005,3796623851&fm=253&fmt=auto&app=138&f=JPEG?w=800&h=500 | finegrained_perception (instance-level) | 19.png | dev | |
3,000,986 | What is the name of this city? | nan | Shanghai | Singapore | New York | Hong Kong | B | celebrity_recognition | https://img1.baidu.com/it/u=3417567412,1560205768&fm=253&fmt=auto&app=138&f=JPEG?w=652&h=300 | finegrained_perception (instance-level) | 20.png | dev | |
3,000,987 | What is the name of this city? | nan | Shanghai | Singapore | New York | Hong Kong | D | celebrity_recognition | https://img2.baidu.com/it/u=1875414189,2982012210&fm=253&fmt=auto&app=138&f=JPEG?w=1805&h=500 | finegrained_perception (instance-level) | 21.png | dev | |
3,000,988 | What is the name of this city? | nan | Shanghai | Hong Kong | London | Singapore | B | celebrity_recognition | https://img1.baidu.com/it/u=4054486737,2232201273&fm=253&fmt=auto&app=138&f=JPEG?w=600&h=400 | finegrained_perception (instance-level) | 22.png | dev | |
3,000,990 | Where is it located? | nan | Shanghai | Hong Kong | Macao | Singapore | C | celebrity_recognition | https://img2.baidu.com/it/u=2859560322,3508306970&fm=253&fmt=auto&app=138&f=JPEG?w=600&h=438 | finegrained_perception (instance-level) | 24.png | dev | |
3,000,991 | Where is this? | nan | Shanghai | Hong Kong | London | Singapore | B | celebrity_recognition | https://img2.baidu.com/it/u=4046451314,608707891&fm=253&fmt=auto&app=138&f=JPEG?w=500&h=679 | finegrained_perception (instance-level) | 25.png | dev | |
3,000,992 | Where is it located? | nan | Abu Dhabi | Riyadh | Doha | Dubai | D | celebrity_recognition | https://img1.baidu.com/it/u=2429866527,255223523&fm=253&fmt=auto&app=138&f=JPEG?w=752&h=500 | finegrained_perception (instance-level) | 26.png | dev | |
3,000,994 | Where is it located? | nan | Shanghai | Singapore | New York | Hong Kong | C | celebrity_recognition | https://img1.baidu.com/it/u=3237536936,791921143&fm=253&fmt=auto&app=138&f=JPEG?w=500&h=755 | finegrained_perception (instance-level) | 28.png | dev | |
3,000,997 | Based on the image, what is the relation between the white horse and the black horse? | nan | The balck horse is behind the white horse | The balck horse is on the top of the white horse | The balck horse is on the bottom of the white horse | The white horse is behind the black horse | D | physical_relation | COCO train2014 | relation_reasoning | 1.png | dev | |
3,000,998 | Based on the image, what is the relation between flowers and vase? | nan | Flowers are behind the vase | Flowers are on the top of the vase | Flowers are on the bottom of the vase | Flowers are in the vase | D | physical_relation | COCO train2014 | relation_reasoning | 2.png | dev | |
3,000,999 | Based on the image, where is the laptop? | nan | The laptop is on the small table | The laptop is next to the small table | The laptop is next to the bed | The laptop is on the bed | A | physical_relation | COCO train2014 | relation_reasoning | 3.png | dev | |
3,001,000 | Where is the zebra | nan | It is on the left | It is on the top | It is on the bottom | It is on the right | D | physical_relation | COCO train2014 | relation_reasoning | 4.png | dev | |
3,001,001 | Based on the image, what is the relation between the white boy and the yellow boy? | nan | The white boy is near to the yellow boy | The white boy on the left of the yellow boy | The white boy is behind the yellow boy | The white boy is facing the yellow boy | D | physical_relation | COCO train2014 | relation_reasoning | 5.png | dev | |
3,001,002 | Which is right? | nan | One washbasin is on the top of the other | Two washbasins are next to each other | One washbasin is on the bottom of the other | Two washbasins are far from each other | B | physical_relation | COCO train2014 | relation_reasoning | 6.png | dev | |
3,001,003 | Where is the man? | nan | The building is next to the man | The building on the right of the man | The building on the left of the man | The building is behind the man | D | physical_relation | COCO train2014 | relation_reasoning | 7.png | dev | |
3,001,004 | Where is the sheep? | nan | The sheep is in the front of the car | The sheep is on the right of the car | The sheep is on the left of the car | The sheep is behind the car | A | physical_relation | COCO train2014 | relation_reasoning | 8.png | dev | |
3,001,005 | Which is right? | nan | The cat is standing on the floor | The cat is jumping on the floor | The cat is running on the floor | The cat is lying on the floor | D | physical_relation | COCO train2014 | relation_reasoning | 9.png | dev | |
3,001,006 | here is the woman? | nan | The woman is on the top right | The woman is in the center | The woman is on the top left | The woman is on the bottom right | D | physical_relation | COCO train2014 | relation_reasoning | 10.png | dev | |
3,001,013 | Which is right? | nan | Two toys are far from each other | Two toys are facing each other | Two toys are backing each other | Two toys are next to each other | D | physical_relation | COCO train2014 | relation_reasoning | 17.png | dev | |
3,001,015 | Which is right? | nan | The man is flying in the sea | The man is on the bottom of the image | The man is flying in the sky | The man is at the right of the image | C | physical_relation | COCO train2014 | relation_reasoning | 19.png | dev | |
3,001,018 | What is the anticipated outcome in this image? | nan | He will escape from the police station | He will be arrested and taken to the police station | He will be visiting the police station voluntarily | He will be released from the police station | B | future_prediction | Internet | logic_reasoning | nan | dev | |
3,001,021 | What is the main event in this image? | nan | He will pass the ball to a teammate | He will shoot the game-winning shot | He will block a game-winning shot | He will miss the game-winning shot | B | future_prediction | Internet | logic_reasoning | nan | dev | |
3,001,025 | What is the achievement in this image? | nan | She will not finish the race | She will finish in the middle of the pack | She will be the first to cross the finish line | She will finish last in the race | C | future_prediction | Internet | logic_reasoning | nan | dev | |
3,001,026 | What is the intended outcome in this image? | nan | She will maintain her current leg muscle size | She will grow her leg muscle | She will undergo surgery to reduce leg muscle | She will lose leg muscle | B | future_prediction | Internet | logic_reasoning | nan | dev | |
3,001,030 | What is the unfortunate outcome in this image? | nan | The glasses will be lost | The glasses will be broken | The glasses will be replaced | The glasses will be fixed | B | future_prediction | Internet | logic_reasoning | nan | dev | |
3,001,031 | What is the transformation in this image? | nan | The ice will remain solid | The ice will melt | The ice will turn into steam | The ice will freeze | B | future_prediction | Internet | logic_reasoning | nan | dev | |
3,001,033 | What is the main event in this image? | nan | The man fails to land and breaks the elevator | The man is stuck in the elevator | The man is repairing the elevator | The man successfully lands and fixes the elevator | A | future_prediction | Internet | logic_reasoning | nan | dev | |
3,001,034 | What is the main event in this image? | nan | The man is flying in the air | The man failed to land on the ground | The man is climbing down from a high place | The man successfully lands on the ground | B | future_prediction | Internet | logic_reasoning | nan | dev | |
3,001,037 | What is the main event in this image? | nan | The target enemy is shooting at someone | The target enemy will be shot | The target enemy is hiding | The target enemy is surrendering | B | future_prediction | Internet | logic_reasoning | nan | dev | |
3,001,038 | What is the transformation in this image? | nan | The water will remain liquid | The water will evaporate | The water will condense | The water will freeze | B | future_prediction | Internet | logic_reasoning | nan | dev | |
3,001,040 | What type of environment is depicted in the picture? | nan | shopping mall | street | forest | home | D | image_scene | coarse_perception | nan | dev | ||
3,001,041 | What type of environment is depicted in the picture? | nan | shopping mall | street | forest | home | D | image_scene | coarse_perception | nan | dev | ||
3,001,042 | What type of environment is depicted in the picture? | nan | shopping mall | street | forest | home | D | image_scene | coarse_perception | nan | dev | ||
3,001,044 | What type of environment is depicted in the picture? | nan | shopping mall | street | forest | home | A | image_scene | coarse_perception | nan | dev | ||
3,001,047 | What type of environment is depicted in the picture? | nan | shopping mall | street | forest | home | B | image_scene | coarse_perception | nan | dev | ||
3,001,048 | What type of environment is depicted in the picture? | nan | shopping mall | street | forest | home | B | image_scene | coarse_perception | nan | dev | ||
3,001,049 | What type of environment is depicted in the picture? | nan | shopping mall | street | forest | home | C | image_scene | coarse_perception | nan | dev | ||
3,001,050 | What type of environment is depicted in the picture? | nan | shopping mall | street | forest | home | C | image_scene | coarse_perception | nan | dev | ||
3,001,053 | What kind of weather is depicted in the picture? | nan | rainy | windy | snowy | sunny | D | image_scene | coarse_perception | nan | dev | ||
3,001,054 | What kind of weather is depicted in the picture? | nan | rainy | windy | snowy | sunny | D | image_scene | coarse_perception | nan | dev | ||
3,001,056 | What kind of weather is depicted in the picture? | nan | rainy | windy | snowy | sunny | A | image_scene | coarse_perception | nan | dev | ||
3,001,057 | What kind of weather is depicted in the picture? | nan | rainy | windy | snowy | sunny | A | image_scene | coarse_perception | nan | dev | ||
3,001,058 | What kind of weather is depicted in the picture? | nan | rainy | windy | snowy | sunny | B | image_scene | coarse_perception | nan | dev | ||
3,001,060 | What kind of weather is depicted in the picture? | nan | rainy | windy | snowy | sunny | B | image_scene | coarse_perception | nan | dev | ||
3,001,061 | What kind of weather is depicted in the picture? | nan | rainy | windy | snowy | sunny | C | image_scene | coarse_perception | nan | dev | ||
3,001,062 | What kind of weather is depicted in the picture? | nan | rainy | windy | snowy | sunny | C | image_scene | coarse_perception | nan | dev | ||
3,001,065 | Can you identify the season in which the picture was taken? | nan | summer | fall | winter | spring | D | image_scene | coarse_perception | nan | dev | ||
3,001,066 | Can you identify the season in which the picture was taken? | nan | summer | fall | winter | spring | D | image_scene | coarse_perception | nan | dev | ||
3,001,067 | Can you identify the season in which the picture was taken? | nan | summer | fall | winter | spring | A | image_scene | coarse_perception | nan | dev | ||
3,001,068 | Can you identify the season in which the picture was taken? | nan | summer | fall | winter | spring | A | image_scene | coarse_perception | nan | dev | ||
3,001,069 | Can you identify the season in which the picture was taken? | nan | summer | fall | winter | spring | A | image_scene | coarse_perception | nan | dev | ||
3,001,072 | Can you identify the season in which the picture was taken? | nan | summer | fall | winter | spring | B | image_scene | coarse_perception | nan | dev | ||
3,001,074 | Can you identify the season in which the picture was taken? | nan | summer | fall | winter | spring | C | image_scene | coarse_perception | nan | dev | ||
3,001,075 | Can you identify the season in which the picture was taken? | nan | summer | fall | winter | spring | C | image_scene | coarse_perception | nan | dev | ||
3,001,076 | Does the picture show a mountainous landscape or a coastal landscape? | nan | Coastal | plain | basin | Mountainous | D | image_scene | coarse_perception | nan | dev |
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