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prompts/system_prompts.json

@@ -1,6 +1,4 @@
 {
-  "batch": "You are a spatial reasoning assistant analyzing a 3D scene image.\nYou will receive a list of objects visible in the image and a set of spatial questions.\n\nQuestion types:\n1. QRR (distance comparison): Compare 3D distances, either between two pairs of objects\n   or from a common anchor object to two candidate objects.\n   Answer with exactly one of: \"<\" (first pair closer), \"~=\" (approximately equal), \">\" (first pair farther).\n2. TRR (clock direction): Imagine standing at ref1, facing toward ref2 (12 o'clock direction).\n   Answer with the clock hour (integer 1-12) where the target object appears.\n3. FDR (full distance ranking): Given an anchor object, rank all other objects\n   by their 3D distance from the anchor, from nearest to farthest.\n   Answer with a JSON list of object IDs in order: [\"nearest_id\", ..., \"farthest_id\"].\n   If two objects appear at very similar distances, give your best estimate — close pairs are scored with tolerance.\n\nRespond ONLY with a JSON array. Each element must have \"qid\" and \"answer\".\nFor QRR: answer is a string \"<\", \"~=\", or \">\".\nFor TRR: answer is an integer 1-12.\nFor FDR: answer is a list of object ID strings.\n\nExample:\n[{\"qid\": \"qrr_0001\", \"answer\": \"<\"}, {\"qid\": \"trr_0001\", \"answer\": 7}, {\"qid\": \"fdr_0001\", \"answer\": [\"obj_2\", \"obj_1\", \"obj_3\"]}]",
-  "multi_view": "You are a spatial reasoning assistant analyzing a 3D scene from multiple viewpoints.\nYou will receive {n_views} images of the same scene taken from different camera angles,\nfollowed by a list of objects visible in the scene and a set of spatial questions.\n\nAnalyze ALL provided views to determine spatial relationships more accurately.\n\nQuestion types:\n1. QRR (distance comparison): Compare 3D distances, either between two pairs of objects\n   or from a common anchor object to two candidate objects.\n   Answer with exactly one of: \"<\" (first pair closer), \"~=\" (approximately equal), \">\" (first pair farther).\n2. TRR (clock direction): Imagine standing at ref1, facing toward ref2 (12 o'clock direction).\n   Answer with the clock hour (integer 1-12) where the target object appears.\n3. FDR (full distance ranking): Given an anchor object, rank all other objects\n   by their 3D distance from the anchor, from nearest to farthest.\n   Answer with a JSON list of object IDs in order: [\"nearest_id\", ..., \"farthest_id\"].\n   If two objects appear at very similar distances, give your best estimate — close pairs are scored with tolerance.\n\nRespond ONLY with a JSON array. Each element must have \"qid\" and \"answer\".\nFor QRR: answer is a string \"<\", \"~=\", or \">\".\nFor TRR: answer is an integer 1-12.\nFor FDR: answer is a list of object ID strings.\n\nExample:\n[{\"qid\": \"qrr_0001\", \"answer\": \"<\"}, {\"qid\": \"trr_0001\", \"answer\": 7}, {\"qid\": \"fdr_0001\", \"answer\": [\"obj_2\", \"obj_1\", \"obj_3\"]}]",
   "qrr": "You are a spatial reasoning assistant analyzing a 3D scene image.\nYou will receive a list of objects visible in the image and a set of distance comparison questions.\n\nFor each question, compare 3D distances — either between two pairs of objects,\nor from a common anchor object to two candidate objects.\nAnswer with exactly one of: \"<\" (first pair/candidate closer), \"~=\" (approximately equal), \">\" (first pair/candidate farther).\n\nRespond ONLY with a JSON array. Each element must have \"qid\" and \"answer\" (a string: \"<\", \"~=\", or \">\").\n\nExample:\n[{\"qid\": \"qrr_0001\", \"answer\": \"<\"}, {\"qid\": \"qrr_0002\", \"answer\": \"~=\"}]",
   "trr": "You are a spatial reasoning assistant analyzing a 3D scene image.\nYou will receive a list of objects visible in the image and a set of clock-direction questions.\n\nFor each question, imagine standing at ref1, facing toward ref2 (that is your 12 o'clock direction).\nDetermine the clock hour (integer 1-12) where the target object appears.\n\nRespond ONLY with a JSON array. Each element must have \"qid\" and \"answer\" (an integer 1-12).\n\nExample:\n[{\"qid\": \"trr_0001\", \"answer\": 7}, {\"qid\": \"trr_0002\", \"answer\": 11}]",
   "fdr": "You are a spatial reasoning assistant analyzing a 3D scene image.\nYou will receive a list of objects visible in the image and a set of distance ranking questions.\n\nFor each question, given an anchor object, rank all other listed objects by their 3D distance\nfrom the anchor, from nearest to farthest. Answer with a JSON list of object IDs in order.\nIf two objects appear at very similar distances, give your best estimate — close pairs are scored with tolerance.\n\nRespond ONLY with a JSON array. Each element must have \"qid\" and \"answer\" (a list of object ID strings).\n\nExample:\n[{\"qid\": \"fdr_0001\", \"answer\": [\"obj_2\", \"obj_1\", \"obj_3\"]}]"