{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"bbeh","formal_name":"BIG-Bench Extra Hard (BBEH)","introduction":"BIG-Bench Extra Hard evaluates language-model reasoning through challenging task categories. It offers full and mini distributions; this import contains the full distribution: 4,520 questions across all 23 task categories.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://github.com/google-deepmind/bbeh","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"029bb740-6062-5e0f-967a-334a4c366fcf","task_key":"bbeh~5fbuggy~5ftables--full--029bb740-6062-5e0f-967a-334a4c366fcf","task_revision_id":"1","upstream_id":"","short_description":"I have a table with 26 rows (including the header) and 18 columns. The table was…","config":"bbeh_buggy_tables","split":"full","body":"{\"input\":\"I have a table with 26 rows (including the header) and 18 columns. The table was saved in a column-major format as follows:\\n\\n[date, 2025-01-27, 2025-01-26, 2025-01-25, 2025-01-24, 2025-01-23, 2025-01-22, 2025-01-21, 2025-01-20, 2025-01-19, 2025-01-18, 2025-01-17, 2025-01-16, 2025-01-15, 2025-01-14, 2025-01-13, 2025-01-12, 2025-01-11, 2025-01-10, 2025-01-09, 2025-01-08, 2025-01-07, 2025-01-06, 2025-01-05, 2025-01-04, 2025-01-03, num_steps, null, null, 6112, 7112, 12941, 5693, null, 6223, 5549, 12054, 9201, 1157, 11888, 14818, 1125, 18636, 11126, 17156, 6867, 688, null, 4861, 9623, 14475, 17981, -3, study_minutes, 17, 75, 10, null, 97, 46, 49, 28, 71, 17, 76, null, 78, 72, 99, 75, 70, 56, 50, 31, 97, 66, 24, 59, 77, 1, 5, exercise_minutes, 34, 92, 36, 60, 87, 99, 18, 36, 19, 20, 50, 75, 93, 50, 59, null, 100, 53, 79, 38, 62, 86, 45, 13, 61, -3, 4, -9, sleep_minutes, 344, null, 435, 435, 461, 445, 452, 439, 499, 461, 557, 506, 460, 366, 586, 404, 365, 345, 447, 404, 370, 326, 361, 503, 385, -7, -7, -8, 7, bed_time, null, 22:39, 22:23, 21:24, 21:45, 21:25, 21:40, 21:14, 22:35, 21:30, 23:42, 21:29, 23:15, 22:55, 23:40, 21:27, 22:57, 23:29, 22:32, 23:20, 23:31, 22:53, 22:17, 23:42, null, 0, -3, 9, 2, -8, num_messages, null, 43, 42, 24, 99, 76, 48, 22, 41, 24, 53, 62, null, 35, 92, 68, 19, 84, 32, 43, 59, 95, 45, 39, 14, 3, -1, -3, -10, 10, -8, num_emails, 4, 8, 2, null, null, 8, 6, 10, 6, 6, 7, 2, 10, 5, 1, 1, 2, 1, 6, 2, 9, 6, 10, 4, 8, -7, 0, -8, 1, 1, 0, -8, num_calls, 10, 8, 1, 6, null, null, 3, 4, 2, 10, 5, 7, 3, 3, 9, 9, 10, 3, 7, 10, null, 4, 4, 1, 7, -7, -6, 10, -6, 10, 8, -6, -5, calories_burned, 231, 371, 722, 284, 661, 291, 606, 326, 123, 783, null, 660, 911, 757, 474, 654, 260, null, 295, 255, 360, 618, 576, 363, 480, 2, 2, 6, 4, 4, -10, 9, 10, 10, weekday, null, null, Wed, Thu, Fri, Sat, Sun, null, Tue, Wed, Thu, null, Sat, Sun, null, Tue, Wed, Thu, Fri, Sat, Sun, Mon, Tue, Wed, Thu, -4, 4, -9, -9, -7, 4, -5, 0, -7, -3, calories_consumed, 1778, 1888, null, 479, 567, 919, 326, 1726, 1062, null, 1789, 1959, 1449, 1908, 1853, 640, 1587, 731, 1600, 488, 1714, 1263, null, 871, 1606, 8, 8, 0, -8, -7, -6, -2, 3, -3, 5, -9, num_meetings, 10, 12, 10, 10, 11, 15, 2, 8, 10, 8, 15, 15, 5, 15, null, 7, 12, 6, 8, 8, 15, 10, 6, 3, 10, 5, -3, -10, 9, 1, 4, 1, 10, 3, 0, 7, -6, coding_minutes, 21, 36, 28, 43, 36, null, 14, 49, 30, 53, 19, 65, 26, 56, 45, null, 26, 53, 2, 8, 39, 7, 39, 22, null, 5, 10, 6, -6, -4, 10, -6, 5, 1, 8, 2, 5, -10, num_tasks_completed, 6, 1, 8, 3, 3, 1, 4, 5, 6, null, 1, 8, 2, 7, 6, 10, null, 4, 1, 10, 8, 8, 7, null, 10, -7, 7, -10, -3, -9, 5, -1, 1, 9, -10, -5, -2, 2, 4, water_intake_ml, 669, 1433, 2217, 1566, 734, 620, 2594, 1194, 2050, 545, 541, 2376, 659, 825, 1869, 773, 1224, null, 2220, 1231, 754, 2008, null, null, 2994, 10, 0, -2, 9, -8, -2, 8, -3, 9, 4, -5, -3, -4, -5, -10, phone_screen_time_minutes, 40, 54, 31, 46, 52, 48, 56, 28, 32, 11, null, 37, 27, 10, null, 43, 49, 37, 31, null, 57, 42, 17, 37, 60, -8, -1, 1, 7, -1, -1, -6, 8, 1, -3, -2, -9, -5, -3, 4, 2, music_listening_minutes, 52, 58, 15, 52, 37, 10, 24, 24, 58, 49, 32, 41, 35, 12, 27, 41, 42, null, null, null, 27, 53, null, 56, null, -4, -3, 4, -1, -3, -5, 7, -3, 2, -8, 8, -9, 7, 7, 8, 6, -5].\\n\\nHowever, the code to save the table was buggy and after saving each column, it appeneded some random values to the end of the column. Specifically, at the end of the i-th column (0-indexed), i random values were appended to the end of the column. Compute the absolute difference between the mean of column sleep_minutes and column coding_minutes, only looking at the days where the number of calories consumed was less than 1800 and the exercise minutes was less than 50. Round the result to 2 decimal places. If it cannot be determined whether the condition is satisfied or not (e.g., due to null values that cannot be inferred from the rest of the table), assume the condition is not satisfied. If a value is null, ignore it from the computations. If any of the means cannot be computed due to there being no values, the final answer must be \\\"0\\\". \"}","display_format":"text","language":"","answer_status":"published","assets":[],"source_url":"https://github.com/google-deepmind/bbeh","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}