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Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type
struct<label: string, taxa: list<item: int64>>
to
{'target': Value('int64')}
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 295, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2281, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2233, in cast_table_to_schema
cast_array_to_feature(
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1804, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2101, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<label: string, taxa: list<item: int64>>
to
{'target': Value('int64')}
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1925, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id string | domain string | task string | question string | answer dict | metadata dict |
|---|---|---|---|---|---|
algebra_REL-A1_00000 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[639.4267984578837, 25.010755222666937, 275.02931836911927]
[223.21073814882274, 736.4712141640124, 676.6994874229113]
[892.1795677048455, 86.93883262941615, 421.9218196852704]
Panel 1:
[639.4267984578837, 25.010755222666937, ... | {
"target": 0
} | {
"panels": [
[
[
639.4267984578837,
25.010755222666937,
275.02931836911927
],
[
223.21073814882274,
736.4712141640124,
676.6994874229113
],
[
892.1795677048455,
86.93883262941615,
421.9218196852704
]
]... |
algebra_REL-A1_00001 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[717.9142707189759, 212.6265440541406, 499.23125949227733]
[884.6831538867025, 642.8518702004242, 142.87159044206265]
[139.6303195255063, 744.9889820916065, 538.9772896672904]
Panel 1:
[717.9142707189759, 212.6265440541406, 49... | {
"target": 6
} | {
"panels": [
[
[
717.9142707189759,
212.6265440541406,
499.23125949227733
],
[
884.6831538867025,
642.8518702004242,
142.87159044206265
],
[
139.6303195255063,
744.9889820916065,
538.9772896672904
]
],... |
algebra_REL-A1_00002 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[539.2960887794584, 729.9310690899762, 201.1510633896959]
[311.71629130089497, 995.1493566608947, 649.8780576394535]
[438.10008391450407, 517.5758410355907, 121.00419586826573]
Panel 1:
[539.2960887794584, 729.9310690899762, 2... | {
"target": 3
} | {
"panels": [
[
[
539.2960887794584,
729.9310690899762,
201.1510633896959
],
[
311.71629130089497,
995.1493566608947,
649.8780576394535
],
[
438.10008391450407,
517.5758410355907,
121.00419586826573
]
]... |
algebra_REL-A1_00003 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[189.89786726763714, 217.70089841417496, 58.483292007299404]
[735.7371787890435, 60.95757147651582, 313.6048097697293]
[50.142337263953564, 476.7885171089349, 919.3871308320753]
Panel 1:
[189.89786726763714, 217.70089841417496... | {
"target": 2
} | {
"panels": [
[
[
189.89786726763714,
217.70089841417496,
58.483292007299404
],
[
735.7371787890435,
60.95757147651582,
313.6048097697293
],
[
50.142337263953564,
476.7885171089349,
919.3871308320753
]
... |
algebra_REL-A1_00004 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[130.81966070170225, 979.797953828836, 161.58197627388614]
[441.83551186085054, 705.6674467599908, 560.9068647747464]
[111.873880589335, 945.0509390466391, 691.0196237558764]
Panel 1:
[130.81966070170225, 979.797953828836, 161... | {
"target": 2
} | {
"panels": [
[
[
130.81966070170225,
979.797953828836,
161.58197627388614
],
[
441.83551186085054,
705.6674467599908,
560.9068647747464
],
[
111.873880589335,
945.0509390466391,
691.0196237558764
]
],
... |
algebra_REL-A1_00005 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[385.1954333447272, 576.5880434965995, 254.72250613858193]
[708.7852838341706, 1.6912782186294661, 925.5751654990827]
[538.4519970927919, 719.4299991448455, 741.9500778394765]
Panel 1:
[385.1954333447272, 576.5880434965995, 25... | {
"target": 3
} | {
"panels": [
[
[
385.1954333447272,
576.5880434965995,
254.72250613858193
],
[
708.7852838341706,
1.6912782186294661,
925.5751654990827
],
[
538.4519970927919,
719.4299991448455,
741.9500778394765
]
],... |
algebra_REL-A1_00006 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[848.3363473516597, 456.4618254701725, 801.4166017222644]
[667.5777325863531, 987.8924530664481, 595.4523184694197]
[950.0396084431559, 891.425925810437, 612.6523227617629]
Panel 1:
[848.3363473516597, 456.4618254701725, 801.4... | {
"target": 6
} | {
"panels": [
[
[
848.3363473516597,
456.4618254701725,
801.4166017222644
],
[
667.5777325863531,
987.8924530664481,
595.4523184694197
],
[
950.0396084431559,
891.425925810437,
612.6523227617629
]
],
... |
algebra_REL-A1_00007 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[326.84580488130854, 761.2297078940271, 379.12621556413626]
[752.0098235547848, 831.9242851552726, 252.2715317823806]
[81.90623276164256, 19.38328705001069, 539.4190479225337]
Panel 1:
[326.84580488130854, 761.2297078940271, 3... | {
"target": 5
} | {
"panels": [
[
[
326.84580488130854,
761.2297078940271,
379.12621556413626
],
[
752.0098235547848,
831.9242851552726,
252.2715317823806
],
[
81.90623276164256,
19.38328705001069,
539.4190479225337
]
],... |
algebra_REL-A1_00008 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[450.8020001937705, 750.4762818270062, 569.8496446783222]
[668.1884704454935, 336.3966198913753, 494.306503615922]
[325.01416788875946, 487.5499323913444, 354.82496617609524]
Panel 1:
[450.8020001937705, 750.4762818270062, 569... | {
"target": 4
} | {
"panels": [
[
[
450.8020001937705,
750.4762818270062,
569.8496446783222
],
[
668.1884704454935,
336.3966198913753,
494.306503615922
],
[
325.01416788875946,
487.5499323913444,
354.82496617609524
]
],
... |
algebra_REL-A1_00009 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[629.4457069519983, 53.609074292533144, 149.19758447365516]
[562.8395970845642, 303.8355118422277, 993.9181227102201]
[118.45156221146158, 764.4434453261943, 606.3176512429628]
Panel 1:
[629.4457069519983, 53.609074292533144, ... | {
"target": 3
} | {
"panels": [
[
[
629.4457069519983,
53.609074292533144,
149.19758447365516
],
[
562.8395970845642,
303.8355118422277,
993.9181227102201
],
[
118.45156221146158,
764.4434453261943,
606.3176512429628
]
]... |
algebra_REL-A1_00010 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[518.9638409876039, 442.22940442020285, 278.1565724424209]
[996.9454749325635, 435.8849870770031, 814.2449445406033]
[969.0552360657036, 470.0103949603517, 408.3480934300153]
Panel 1:
[518.9638409876039, 442.22940442020285, 27... | {
"target": 5
} | {
"panels": [
[
[
518.9638409876039,
442.22940442020285,
278.1565724424209
],
[
996.9454749325635,
435.8849870770031,
814.2449445406033
],
[
969.0552360657036,
470.0103949603517,
408.3480934300153
]
],
... |
algebra_REL-A1_00011 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[998.9023332293388, 489.640346655701, 148.59541838278912]
[538.5805777038737, 345.1239416930075, 551.917417070811]
[543.430062958673, 455.3446168665011, 321.77735022903744]
Panel 1:
[998.9023332293388, 489.640346655701, 148.59... | {
"target": 3
} | {
"panels": [
[
[
998.9023332293388,
489.640346655701,
148.59541838278912
],
[
538.5805777038737,
345.1239416930075,
551.917417070811
],
[
543.430062958673,
455.3446168665011,
321.77735022903744
]
],
... |
algebra_REL-A1_00012 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[683.1345799627139, 497.66725236795105, 583.157130652053]
[232.1884442951523, 637.9046310035685, 459.570499176731]
[666.8407172664807, 898.9085317003211, 465.2532555253015]
Panel 1:
[683.1345799627139, 497.66725236795105, 583.... | {
"target": 4
} | {
"panels": [
[
[
683.1345799627139,
497.66725236795105,
583.157130652053
],
[
232.1884442951523,
637.9046310035685,
459.570499176731
],
[
666.8407172664807,
898.9085317003211,
465.2532555253015
]
],
... |
algebra_REL-A1_00013 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[966.5002094627521, 860.1405968988219, 724.2167120755182]
[979.9422427819035, 967.2697473000323, 804.5876440205619]
[365.7750494055664, 790.6819685889375, 13.918655100901178]
Panel 1:
[966.5002094627521, 860.1405968988219, 724... | {
"target": 1
} | {
"panels": [
[
[
966.5002094627521,
860.1405968988219,
724.2167120755182
],
[
979.9422427819035,
967.2697473000323,
804.5876440205619
],
[
365.7750494055664,
790.6819685889375,
13.918655100901178
]
],
... |
algebra_REL-A1_00014 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[215.95135191867476, 869.6954267695447, 328.5595534322304]
[147.55417994144372, 900.5310356317582, 2.8355514800163517]
[858.4061263801764, 144.687980320508, 129.9921314434368]
Panel 1:
[215.95135191867476, 869.6954267695447, 3... | {
"target": 4
} | {
"panels": [
[
[
215.95135191867476,
869.6954267695447,
328.5595534322304
],
[
147.55417994144372,
900.5310356317582,
2.8355514800163517
],
[
858.4061263801764,
144.687980320508,
129.9921314434368
]
],... |
algebra_REL-A1_00015 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[431.8765185517403, 744.588969191879, 372.6468593759036]
[130.11545357384335, 59.98097797084656, 956.6246238469065]
[561.6833815697281, 670.0132647322959, 410.8086329221582]
Panel 1:
[431.8765185517403, 744.588969191879, 372.6... | {
"target": 6
} | {
"panels": [
[
[
431.8765185517403,
744.588969191879,
372.6468593759036
],
[
130.11545357384335,
59.98097797084656,
956.6246238469065
],
[
561.6833815697281,
670.0132647322959,
410.8086329221582
]
],
... |
algebra_REL-A1_00016 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[7.687085899882873, 301.4193620184368, 211.23397922031228]
[137.234805257327, 255.51950402145928, 328.1223559378411]
[7.7299065693119395, 747.0141234297678, 175.6948018758423]
Panel 1:
[7.687085899882873, 301.4193620184368, 21... | {
"target": 6
} | {
"panels": [
[
[
7.687085899882873,
301.4193620184368,
211.23397922031228
],
[
137.234805257327,
255.51950402145928,
328.1223559378411
],
[
7.7299065693119395,
747.0141234297678,
175.6948018758423
]
],... |
algebra_REL-A1_00017 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[351.94222262007656, 74.19065617328768, 461.7424864464541]
[37.60724557109207, 368.7375994898128, 287.0770326013192]
[644.6664695758374, 977.3685325331492, 90.29650401330281]
Panel 1:
[351.94222262007656, 74.19065617328768, 46... | {
"target": 6
} | {
"panels": [
[
[
351.94222262007656,
74.19065617328768,
461.7424864464541
],
[
37.60724557109207,
368.7375994898128,
287.0770326013192
],
[
644.6664695758374,
977.3685325331492,
90.29650401330281
]
],
... |
algebra_REL-A1_00018 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[226.54304653388724, 137.5653531770793, 77.16508430087632]
[844.4283886858833, 101.14076366789415, 770.874720363101]
[835.1198266345559, 883.6821654925616, 37.74749235756125]
Panel 1:
[226.54304653388724, 137.5653531770793, 77... | {
"target": 5
} | {
"panels": [
[
[
226.54304653388724,
137.5653531770793,
77.16508430087632
],
[
844.4283886858833,
101.14076366789415,
770.874720363101
],
[
835.1198266345559,
883.6821654925616,
37.74749235756125
]
],
... |
algebra_REL-A1_00019 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[472.45493304783093, 831.1104859321764, 758.8411547656073]
[469.11012715549373, 615.3482571635484, 905.8574891032708]
[19.00388491097038, 215.6547444683544, 149.51961896422682]
Panel 1:
[472.45493304783093, 831.1104859321764, ... | {
"target": 6
} | {
"panels": [
[
[
472.45493304783093,
831.1104859321764,
758.8411547656073
],
[
469.11012715549373,
615.3482571635484,
905.8574891032708
],
[
19.00388491097038,
215.6547444683544,
149.51961896422682
]
]... |
algebra_REL-A1_00020 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[780.841566978425, 865.7982770780576, 331.92468638134454]
[124.4750082443834, 368.019174314673, 889.4865170122814]
[743.3077055196212, 894.6374949550533, 386.64476826069216]
Panel 1:
[780.841566978425, 865.7982770780576, 331.9... | {
"target": 2
} | {
"panels": [
[
[
780.841566978425,
865.7982770780576,
331.92468638134454
],
[
124.4750082443834,
368.019174314673,
889.4865170122814
],
[
743.3077055196212,
894.6374949550533,
386.64476826069216
]
],
... |
algebra_REL-A1_00021 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[852.8262903843226, 452.04268524539737, 898.6790307862303]
[445.11119274245505, 87.79074110473107, 681.9292602506372]
[845.5212189746994, 319.58777209997015, 347.42529473856456]
Panel 1:
[852.8262903843226, 452.04268524539737,... | {
"target": 1
} | {
"panels": [
[
[
852.8262903843226,
452.04268524539737,
898.6790307862303
],
[
445.11119274245505,
87.79074110473107,
681.9292602506372
],
[
845.5212189746994,
319.58777209997015,
347.42529473856456
]
... |
algebra_REL-A1_00022 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[41.19430352178411, 863.781191620033, 81.22285489336988]
[948.5468539703916, 771.0223687944653, 264.65590783305447]
[210.80837970196453, 572.1372024460642, 618.1084263249576]
Panel 1:
[41.19430352178411, 863.781191620033, 81.2... | {
"target": 0
} | {
"panels": [
[
[
41.19430352178411,
863.781191620033,
81.22285489336988
],
[
948.5468539703916,
771.0223687944653,
264.65590783305447
],
[
210.80837970196453,
572.1372024460642,
618.1084263249576
]
],
... |
algebra_REL-A1_00023 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[73.53174974284182, 504.2555291232047, 764.4041147072396]
[279.720677623982, 989.0907006207226, 680.3986401188607]
[118.81101972358954, 975.082815413784, 393.90371272860716]
Panel 1:
[73.53174974284182, 504.2555291232047, 764.... | {
"target": 5
} | {
"panels": [
[
[
73.53174974284182,
504.2555291232047,
764.4041147072396
],
[
279.720677623982,
989.0907006207226,
680.3986401188607
],
[
118.81101972358954,
975.082815413784,
393.90371272860716
]
],
... |
algebra_REL-A1_00024 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[376.8247761856958, 956.6854921965481, 459.66353201958657]
[533.127064573221, 546.2732192448302, 675.868576556368]
[867.6544034549934, 680.7458895691416, 803.6525301137067]
Panel 1:
[376.8247761856958, 956.6854921965481, 459.6... | {
"target": 4
} | {
"panels": [
[
[
376.8247761856958,
956.6854921965481,
459.66353201958657
],
[
533.127064573221,
546.2732192448302,
675.868576556368
],
[
867.6544034549934,
680.7458895691416,
803.6525301137067
]
],
... |
algebra_REL-A1_00025 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[175.0647754809631, 882.2449731648331, 175.78870753886255]
[919.6348118509339, 997.1718030885099, 396.99457427829964]
[495.3838973217578, 936.6087447777628, 962.1313800833424]
Panel 1:
[175.0647754809631, 882.2449731648331, 17... | {
"target": 4
} | {
"panels": [
[
[
175.0647754809631,
882.2449731648331,
175.78870753886255
],
[
919.6348118509339,
997.1718030885099,
396.99457427829964
],
[
495.3838973217578,
936.6087447777628,
962.1313800833424
]
],... |
algebra_REL-A1_00026 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[664.0944393396638, 218.41162265732595, 247.46542930857774]
[754.7395497248654, 873.1350584877333, 81.87030647327487]
[446.7479774964833, 703.7661251558726, 78.10272214744019]
Panel 1:
[664.0944393396638, 218.41162265732595, 2... | {
"target": 1
} | {
"panels": [
[
[
664.0944393396638,
218.41162265732595,
247.46542930857774
],
[
754.7395497248654,
873.1350584877333,
81.87030647327487
],
[
446.7479774964833,
703.7661251558726,
78.10272214744019
]
],... |
algebra_REL-A1_00027 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[937.4103611350669, 725.0239459089183, 112.84463876647732]
[809.4781835391944, 419.2405984917521, 766.0534675139033]
[883.7566218453745, 15.645796363549568, 206.08162185021416]
Panel 1:
[937.4103611350669, 725.0239459089183, 1... | {
"target": 1
} | {
"panels": [
[
[
937.4103611350669,
725.0239459089183,
112.84463876647732
],
[
809.4781835391944,
419.2405984917521,
766.0534675139033
],
[
883.7566218453745,
15.645796363549568,
206.08162185021416
]
]... |
algebra_REL-A1_00028 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[587.583688827643, 671.4505222354119, 217.0165216877624]
[208.8890885522503, 907.0328275335155, 303.18802563115764]
[908.9941607068009, 211.80777204900804, 190.0236976301487]
Panel 1:
[587.583688827643, 671.4505222354119, 217.... | {
"target": 1
} | {
"panels": [
[
[
587.583688827643,
671.4505222354119,
217.0165216877624
],
[
208.8890885522503,
907.0328275335155,
303.18802563115764
],
[
908.9941607068009,
211.80777204900804,
190.0236976301487
]
],
... |
algebra_REL-A1_00029 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[933.9037210980009, 912.7514547348331, 659.2843419898627]
[15.731766869219733, 532.2124850127366, 411.33850821741646]
[16.726147602629915, 722.1927216257209, 535.7381029239248]
Panel 1:
[933.9037210980009, 912.7514547348331, 6... | {
"target": 4
} | {
"panels": [
[
[
933.9037210980009,
912.7514547348331,
659.2843419898627
],
[
15.731766869219733,
532.2124850127366,
411.33850821741646
],
[
16.726147602629915,
722.1927216257209,
535.7381029239248
]
]... |
algebra_REL-A1_00030 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[988.4779579141031, 724.1635700943149, 500.7928516377251]
[974.3233274359964, 53.6964319473936, 437.08825284349916]
[838.674657613175, 340.59274647510597, 769.0056533654423]
Panel 1:
[988.4779579141031, 724.1635700943149, 500.... | {
"target": 6
} | {
"panels": [
[
[
988.4779579141031,
724.1635700943149,
500.7928516377251
],
[
974.3233274359964,
53.6964319473936,
437.08825284349916
],
[
838.674657613175,
340.59274647510597,
769.0056533654423
]
],
... |
algebra_REL-A1_00031 | algebra | REL-A1 | Complete the Raven's progressive matrix. Only return the missing panel index (1-8)!
Panel 0:
[379.8899561470482, 862.1983105655142, 440.2229214812533]
[430.6162209471722, 823.5352401398752, 651.0368583666188]
[594.3929190644955, 300.4352846791234, 603.211268389813]
Panel 1:
[379.8899561470482, 862.1983105655142, 440.2... | {
"target": 3
} | {
"panels": [
[
[
379.8899561470482,
862.1983105655142,
440.2229214812533
],
[
430.6162209471722,
823.5352401398752,
651.0368583666188
],
[
594.3929190644955,
300.4352846791234,
603.211268389813
]
],
... |
Evaluating Relational Reasoning in LLMs with REL
Authors: Lukas Fesser*, Yasha Ektefaie*, Ada Fang*, Sham M. Kakakde, Marinka Zitnik
* indicates equal contribution
Read our preprint here.
This repository contains the REL benchmarks for chemistry, biology, and algebra. For evaluation scripts please refer to our GitHub repo.
Algebra (1,000 questions)
All algebra tasks are Raven's Progressive Matrices: complete a 3×3 or 9×9 grid of number tuples by identifying the missing panel from 8 candidates. The matrix sizes differ in context length and difficulty.
| Task | RC | RC min | RC max | Size | Questions | Assesses |
|---|---|---|---|---|---|---|
| REL-A1 | 2 | 2 | 2 | 3×3 and 9×9 | 125 each | Constant rows — each row is identical; tests whether the model recognizes invariance |
| REL-A2 | 2 | 2 | 2 | 3×3 and 9×9 | 125 each | Arithmetic progression — values shift by a fixed increment across rows; tests detection of linear trends |
| REL-A3 | $n$ where $n\times n$ is the matrix size | 3 | 9 | 3×3 and 9×9 | 125 each | Permutation — each row is a cyclic permutation of the same values; tests recognition of reordering patterns |
| REL-A4 | $n$ where $n\times n$ is the matrix size | 3 | 9 | 3×3 and 9×9 | 125 each | Row-Sum — the final value in each row is the sum of all other entries in the same row multiplied by either $\pm1$, depending on the column. |
Biology (7,952 questions)
All biology tasks are REL-B1, split across 12 files by phylogenetic tree/alignment instance. Each question presents a multiple sequence alignment (FASTA) and a phylogenetic tree, and asks whether structured homoplasy is present and which taxa are involved.
| Task | RC | RC min | RC max | Files | Total questions | Assesses |
|---|---|---|---|---|---|---|
| REL-B1 | Number of homoplastic taxa | 2 | 25 | 001–012 | 7,952 | Homoplasy detection — identifying convergent evolution where distantly related taxa independently share nucleotide motifs across many alignment columns more than expected by chance; tests relational pattern recognition over long biological sequences |
Chemistry (4,016 questions)
| Task | RC | RC min | RC max | Questions | Assesses |
|---|---|---|---|---|---|
| REL-C1 | 2 | 2 | 2 | 1,000 | Constitutional isomer identification — given a set of SMILES, determine whether all molecules share the same molecular formula (same atoms, different connectivity); tests recognition of molecular equivalence relations |
| REL-C2 | 2 | 2 | 2 | 1,016 | Maximum common substructure (MCS) — find the largest single connected chemical motif present in every molecule in the set; tests relational reasoning over graph structure |
| REL-C3 | Number of isomers | 1 | 92 | 1,000 | Isomer set completion — given a partial set of constitutional isomers, identify all missing members; tests exhaustive enumeration of a structural equivalence class |
| REL-C4 | Number of molecules | 5 | 50 | 1,000 | Constrained motif extraction — extract one substructure from each of the molecules such that a specified functional group count sums to a target value; tests joint constraint satisfaction over molecular substructures |
Citation
@article{fesser2026rel,
title = {Evaluating Relational Reasoning in LLMs with REL},
author = {Lukas Fesser and Yasha Ektefaie and Ada Fang and Sham M. Kakade and Marinka Zitnik},
year = {2026},
journal = {arXiv preprint arXiv:2604.12176},
eprint = {2604.12176},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2604.12176}
}
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