{"taskset": {"n_runnable": 0, "name": null, "url_data": null, "catalog_id": null, "owner_type": null, "cited_by": null, "taskset": "locomo", "domain": "reasoning-knowledge", "task_kind": null, "environment": null, "grading": null, "path": "datasets/locomo", "n_single_container": 10, "n_tasks": 10, "domain_raw": null, "sample_instruction": "The full multi-session conversation transcript for this task is in `/app/conversation.md`. Read it carefully before answering the questions below.\n\nThe preamble at the top of `/app/conversation.md` names the two speakers and explains the date markers. The body is a chronological transcript across multiple sessions.\n\nBased on the conversation in `/app/conversation.md`, write short answers for each of the following questions in a few words. Write the answers in the form of a JSON object where each entry contains the question number as `\"key\"` (a string) and the short answer as `\"value\"`. Use single-quote characters for named entities and double-quote characters for enclosing JSON elements. Answer with exact words from the conversation whenever possible.\n\nWrite the resulting JSON object to `/workspace/answers.json`. Example:\n\n```json\n{\n  \"0\": \"7 May 2023\",\n  \"1\": \"mental health\"\n}\n```\n\nQuestions:\n\n0: When did Caroline go to the LGBTQ support group? Use DATE of CONVERSATION to answer with an approximate date.\n1: When did Melanie paint a sunrise? Use DATE of CONVERSATION to answer with an approximate date.\n2: What fields would Caroline be likely to pursue in her educaton?\n3: What did Caroline research?\n4: What is Caroline's identity?\n5: When did Melanie run a charity race? Use DATE of CONVERSATION to answer with an approximate date.\n6: When is Melanie planning on going camping? Use DATE of CONVERSATION to answer with an approximate date.\n7: What is Caroline's relationship status?\n", "owner_org": null, "url_repo": null, "url_paper": null, "license": null, "languages": [], "difficulties": {"hard": 10}, "categories": ["memory-qa"]}, "tasks": [{"agent_timeout": 5400, "category": "memory-qa", "compose": false, "difficulty": "hard", "language": "", "oracle": null, "runnable": false, "tags": [], "task": "locomo_conv-26", "taskset": "locomo"}, {"agent_timeout": 5400, "category": "memory-qa", "compose": false, "difficulty": "hard", "language": "", "oracle": null, "runnable": false, "tags": [], "task": "locomo_conv-30", "taskset": "locomo"}, {"agent_timeout": 5400, "category": "memory-qa", "compose": false, "difficulty": "hard", "language": "", "oracle": null, "runnable": false, "tags": [], "task": "locomo_conv-41", "taskset": "locomo"}, {"agent_timeout": 5400, "category": "memory-qa", "compose": false, "difficulty": "hard", "language": "", "oracle": null, "runnable": false, "tags": [], "task": "locomo_conv-42", "taskset": "locomo"}, {"agent_timeout": 5400, "category": "memory-qa", "compose": false, "difficulty": "hard", "language": "", "oracle": null, "runnable": false, "tags": [], "task": "locomo_conv-43", "taskset": "locomo"}, {"agent_timeout": 5400, "category": "memory-qa", "compose": false, "difficulty": "hard", "language": "", "oracle": null, "runnable": false, "tags": [], "task": "locomo_conv-44", "taskset": "locomo"}, {"agent_timeout": 5400, "category": "memory-qa", "compose": false, "difficulty": "hard", "language": "", "oracle": null, "runnable": false, "tags": [], "task": "locomo_conv-47", "taskset": "locomo"}, {"agent_timeout": 5400, "category": "memory-qa", "compose": false, "difficulty": "hard", "language": "", "oracle": null, "runnable": false, "tags": [], "task": "locomo_conv-48", "taskset": "locomo"}, {"agent_timeout": 5400, "category": "memory-qa", "compose": false, "difficulty": "hard", "language": "", "oracle": null, "runnable": false, "tags": [], "task": "locomo_conv-49", "taskset": "locomo"}, {"agent_timeout": 5400, "category": "memory-qa", "compose": false, "difficulty": "hard", "language": "", "oracle": null, "runnable": false, "tags": [], "task": "locomo_conv-50", "taskset": "locomo"}], "next": null}