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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ValueError
Message: Not able to read records in the JSON file at hf://datasets/DGurgurov/conceptnet_all@4968f9546d35964a2cd55268bfa568e8ad74ffeb/cn_relations_clean.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['ab', 'adx', 'ae', 'af', 'ang', 'ar', 'arc', 'arn', 'ast', 'av', 'az', 'ba', 'bal', 'be', 'bg', 'bm', 'bn', 'bo', 'br', 'ca', 'ce', 'ceb', 'chk', 'cim', 'cop', 'crh', 'cs', 'csb', 'cu', 'cy', 'da', 'de', 'dsb', 'ee', 'egl', 'egx', 'egy', 'el', 'en', 'enm', 'eo', 'es', 'et', 'eu', 'fa', 'fi', 'fil', 'fj', 'fo', 'fr', 'frm', 'fro', 'frp', 'frr', 'fur', 'fy', 'ga', 'gag', 'gd', 'gl', 'gml', 'got', 'grc', 'gu', 'gv', 'haw', 'hbo', 'he', 'hi', 'hil', 'hsb', 'ht', 'hu', 'hy', 'ia', 'io', 'is', 'ist', 'it', 'iu', 'ja', 'ka', 'khb', 'ki', 'kjh', 'kk', 'kl', 'km', 'ko', 'koy', 'ku', 'kw', 'ky', 'la', 'lad', 'lb', 'li', 'lij', 'lld', 'lmo', 'ln', 'lo', 'lt', 'lv', 'mdf', 'mg', 'mga', 'mi', 'mk', 'mn', 'ms', 'mt', 'mul', 'mwl', 'my', 'myv', 'nap', 'nci', 'nds', 'nl', 'no', 'nog', 'non', 'nov', 'nrf', 'nv', 'oc', 'oge', 'osp', 'ota', 'pal', 'pcd', 'pi', 'pjt', 'pl', 'ppl', 'pro', 'ps', 'pt', 'rm', 'ro', 'roa-opt', 'rom', 'ru', 'rue', 'rup', 'rw', 'sa', 'scn', 'sco', 'se', 'ses', 'sga', 'sh', 'sk', 'sl', 'sm', 'so', 'sq', 'stq', 'su', 'sv', 'sw', 'swb', 'syc', 'szl', 'ta', 'te', 'tg', 'th', 'tk', 'tpi', 'tpw', 'tr', 'tt', 'ty', 'tyv', 'ug', 'uk', 'ur', 'uz', 'vec', 'vep', 'vi', 'vo', 'vot', 'wa', 'wau', 'wo', 'wym', 'xcl', 'yi', 'yua', 'za', 'zh', 'zza', 'abe', 'ady', 'ain', 'akk', 'akz', 'alt', 'an', 'axm', 'ccc', 'ch', 'chl', 'cho', 'chr', 'cic', 'cjs', 'cv', 'dlm', 'dum', 'esu', 'ff', 'gmh', 'gn', 'goh', 'gsw', 'ha', 'hit', 'ie', 'ii', 'ilo', 'jv', 'kbd', 'kn', 'krl', 'liv', 'lkt', 'ltg', 'lzz', 'mch', 'mh', 'ml', 'mr', 'na', 'nah', 'nan', 'ne', 'nhn', 'nmn', 'odt', 'ofs', 'oj', 'or', 'orv', 'os', 'osx', 'pa', 'pap', 'peo', 'pms', 'qu', 'raj', 'rap', 'sah', 'sc', 'sd', 'si', 'smn', 'sms', 'srn', 'sux', 'tet', 'twf', 'txb', 'uga', 'war', 'xh', 'xmf', 'xpr', 'xwo', 'yo', 'zu', 'co', 'prg', 'aii', 'am', 'bi', 'dv', 'kim', 'krc', 'kum', 'ti', 'udm', 'xto', 'zdj', 'dak', 'frk', 'oma', 'shh', 'aa', 'dje', 'hke', 'qya', 'st', 'wae', 'xno', 'dua', 'fon', 'hak', 'jbo']. Select the correct one and provide it as `field='XXX'` to the dataset loading method.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 241, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2216, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1239, in _head
return _examples_to_batch(list(self.take(n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1389, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1044, in __iter__
yield from islice(self.ex_iterable, self.n)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__
for key, pa_table in self.generate_tables_fn(**self.kwargs):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 170, in _generate_tables
raise ValueError(
ValueError: Not able to read records in the JSON file at hf://datasets/DGurgurov/conceptnet_all@4968f9546d35964a2cd55268bfa568e8ad74ffeb/cn_relations_clean.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['ab', 'adx', 'ae', 'af', 'ang', 'ar', 'arc', 'arn', 'ast', 'av', 'az', 'ba', 'bal', 'be', 'bg', 'bm', 'bn', 'bo', 'br', 'ca', 'ce', 'ceb', 'chk', 'cim', 'cop', 'crh', 'cs', 'csb', 'cu', 'cy', 'da', 'de', 'dsb', 'ee', 'egl', 'egx', 'egy', 'el', 'en', 'enm', 'eo', 'es', 'et', 'eu', 'fa', 'fi', 'fil', 'fj', 'fo', 'fr', 'frm', 'fro', 'frp', 'frr', 'fur', 'fy', 'ga', 'gag', 'gd', 'gl', 'gml', 'got', 'grc', 'gu', 'gv', 'haw', 'hbo', 'he', 'hi', 'hil', 'hsb', 'ht', 'hu', 'hy', 'ia', 'io', 'is', 'ist', 'it', 'iu', 'ja', 'ka', 'khb', 'ki', 'kjh', 'kk', 'kl', 'km', 'ko', 'koy', 'ku', 'kw', 'ky', 'la', 'lad', 'lb', 'li', 'lij', 'lld', 'lmo', 'ln', 'lo', 'lt', 'lv', 'mdf', 'mg', 'mga', 'mi', 'mk', 'mn', 'ms', 'mt', 'mul', 'mwl', 'my', 'myv', 'nap', 'nci', 'nds', 'nl', 'no', 'nog', 'non', 'nov', 'nrf', 'nv', 'oc', 'oge', 'osp', 'ota', 'pal', 'pcd', 'pi', 'pjt', 'pl', 'ppl', 'pro', 'ps', 'pt', 'rm', 'ro', 'roa-opt', 'rom', 'ru', 'rue', 'rup', 'rw', 'sa', 'scn', 'sco', 'se', 'ses', 'sga', 'sh', 'sk', 'sl', 'sm', 'so', 'sq', 'stq', 'su', 'sv', 'sw', 'swb', 'syc', 'szl', 'ta', 'te', 'tg', 'th', 'tk', 'tpi', 'tpw', 'tr', 'tt', 'ty', 'tyv', 'ug', 'uk', 'ur', 'uz', 'vec', 'vep', 'vi', 'vo', 'vot', 'wa', 'wau', 'wo', 'wym', 'xcl', 'yi', 'yua', 'za', 'zh', 'zza', 'abe', 'ady', 'ain', 'akk', 'akz', 'alt', 'an', 'axm', 'ccc', 'ch', 'chl', 'cho', 'chr', 'cic', 'cjs', 'cv', 'dlm', 'dum', 'esu', 'ff', 'gmh', 'gn', 'goh', 'gsw', 'ha', 'hit', 'ie', 'ii', 'ilo', 'jv', 'kbd', 'kn', 'krl', 'liv', 'lkt', 'ltg', 'lzz', 'mch', 'mh', 'ml', 'mr', 'na', 'nah', 'nan', 'ne', 'nhn', 'nmn', 'odt', 'ofs', 'oj', 'or', 'orv', 'os', 'osx', 'pa', 'pap', 'peo', 'pms', 'qu', 'raj', 'rap', 'sah', 'sc', 'sd', 'si', 'smn', 'sms', 'srn', 'sux', 'tet', 'twf', 'txb', 'uga', 'war', 'xh', 'xmf', 'xpr', 'xwo', 'yo', 'zu', 'co', 'prg', 'aii', 'am', 'bi', 'dv', 'kim', 'krc', 'kum', 'ti', 'udm', 'xto', 'zdj', 'dak', 'frk', 'oma', 'shh', 'aa', 'dje', 'hke', 'qya', 'st', 'wae', 'xno', 'dua', 'fon', 'hak', 'jbo']. Select the correct one and provide it as `field='XXX'` to the dataset loading method.Need help to make the dataset viewer work? Open a discussion for direct support.
Clean ConceptNet Data for All Languages
Data Details
For our project on Retrofitting Glove embeddings for Low Resource Languages, we extracted all data from the ConceptNet database for 304 languages. The extraction process involved several steps to clean and analyze the data from the official ConceptNet dump available here.
The final extracted dataset is a JSON file representing a dictionary with language codes and start and end edges for each language. Start edges represent the unique words in a target language, while end edges are the words related to the start edges through various types of relationships. The relationship types and sources are not extracted.
Dataset Structure
cn_relations_clean.json:
{ 'language_iso_code_1':{'start_edge_word_1':['end_edge_word_1', 'end_edge_word_2', ...], ...}, ... }
Dataset Details
| Language Code | Start Edges | End Edges |
|---|---|---|
| ab | 252 | 470 |
| adx | 549 | 884 |
| ae | 192 | 583 |
| af | 12973 | 27263 |
| ang | 9788 | 42140 |
| ar | 75684 | 148744 |
| arc | 1688 | 4555 |
| arn | 1181 | 2540 |
| ast | 27485 | 35625 |
| av | 172 | 256 |
| az | 13277 | 20363 |
| ba | 4250 | 15745 |
| bal | 370 | 877 |
| be | 14871 | 20806 |
| bg | 171740 | 203272 |
| bm | 2422 | 6082 |
| bn | 7306 | 10979 |
| bo | 2127 | 5961 |
| br | 11665 | 19923 |
| ca | 82706 | 182331 |
| ce | 2311 | 2994 |
| ceb | 18882 | 46877 |
| chk | 724 | 1251 |
| cim | 889 | 1842 |
| cop | 1071 | 4606 |
| crh | 2449 | 5064 |
| cs | 77422 | 195513 |
| csb | 602 | 1169 |
| cu | 7526 | 13555 |
| cy | 13243 | 25507 |
| da | 46600 | 91833 |
| de | 500260 | 1682740 |
| dsb | 3993 | 8395 |
| ee | 571 | 934 |
| egl | 854 | 2892 |
| egx | 1890 | 7189 |
| egy | 447 | 516 |
| el | 39667 | 112012 |
| en | 941858 | 5123286 |
| enm | 17286 | 38396 |
| eo | 91074 | 143024 |
| es | 646097 | 945036 |
| et | 20088 | 34980 |
| eu | 41427 | 75928 |
| fa | 46736 | 89120 |
| fi | 259852 | 589931 |
| fil | 16165 | 38613 |
| fj | 209 | 452 |
| fo | 10513 | 32922 |
| fr | 1449790 | 3871820 |
| frm | 4472 | 10636 |
| fro | 14493 | 41614 |
| frp | 2799 | 9840 |
| frr | 476 | 1743 |
| fur | 2295 | 9386 |
| fy | 7608 | 15078 |
| ga | 29459 | 79505 |
| gag | 505 | 841 |
| gd | 14418 | 41729 |
| gl | 52824 | 95824 |
| gml | 177 | 722 |
| got | 2982 | 8258 |
| grc | 25689 | 69250 |
| gu | 4427 | 11282 |
| gv | 6812 | 22512 |
| haw | 1371 | 4768 |
| hbo | 2898 | 3824 |
| he | 27283 | 52365 |
| hi | 18363 | 52422 |
| hil | 1414 | 3544 |
| hsb | 25778 | 26913 |
| ht | 2699 | 4685 |
| hu | 65163 | 138230 |
| hy | 23434 | 63055 |
| ia | 5728 | 8835 |
| io | 21076 | 48758 |
| is | 40287 | 90890 |
| ist | 422 | 1792 |
| it | 548767 | 975877 |
| iu | 1871 | 4031 |
| ja | 283049 | 1473713 |
| ka | 25014 | 44660 |
| khb | 297 | 1053 |
| ki | 1374 | 3873 |
| kjh | 482 | 1412 |
| kk | 13700 | 20243 |
| kl | 1427 | 2814 |
| km | 3466 | 14703 |
| ko | 30616 | 57974 |
| koy | 205 | 423 |
| ku | 9737 | 16008 |
| kw | 1797 | 3754 |
| ky | 3574 | 4570 |
| la | 848943 | 1103644 |
| lad | 1453 | 3239 |
| lb | 10863 | 27341 |
| li | 485 | 1284 |
| lij | 1331 | 3760 |
| lld | 4884 | 6479 |
| lmo | 2109 | 2388 |
| ln | 4109 | 10005 |
| lo | 1422 | 5289 |
| lt | 21184 | 31588 |
| lv | 30059 | 84061 |
| mdf | 2086 | 3301 |
| mg | 26575 | 28503 |
| mga | 178 | 582 |
| mi | 945 | 2503 |
| mk | 28935 | 47833 |
| mn | 6740 | 16462 |
| ms | 88416 | 236012 |
| mt | 2006 | 4933 |
| mul | 16034 | 425333 |
| mwl | 1302 | 1975 |
| my | 4875 | 9251 |
| myv | 642 | 1492 |
| nap | 1506 | 2754 |
| nci | 3358 | 9871 |
| nds | 5192 | 12205 |
| nl | 138580 | 347510 |
| no | 94946 | 173186 |
| nog | 450 | 676 |
| non | 4079 | 12588 |
| nov | 649 | 1523 |
| nrf | 9724 | 31582 |
| nv | 6333 | 19455 |
| oc | 22113 | 42380 |
| oge | 438 | 936 |
| osp | 458 | 1332 |
| ota | 834 | 2604 |
| pal | 256 | 808 |
| pcd | 1424 | 3367 |
| pi | 1828 | 3774 |
| pjt | 364 | 718 |
| pl | 139396 | 227321 |
| ppl | 268 | 740 |
| pro | 2798 | 5015 |
| ps | 1087 | 2423 |
| pt | 248669 | 502566 |
| rm | 3919 | 12959 |
| ro | 36206 | 95016 |
| rom | 552 | 1011 |
| ru | 424944 | 672836 |
| rue | 200 | 447 |
| rup | 3079 | 17106 |
| rw | 355 | 525 |
| sa | 5789 | 26810 |
| scn | 4749 | 8161 |
| sco | 8537 | 14598 |
| se | 68758 | 82605 |
| ses | 3095 | 5790 |
| sga | 2913 | 8507 |
| sh | 57974 | 122601 |
| sk | 21657 | 32058 |
| sl | 89210 | 110311 |
| sm | 588 | 1124 |
| so | 593 | 781 |
| sq | 16262 | 42776 |
| stq | 1237 | 4562 |
| su | 2514 | 2802 |
| sv | 133965 | 253397 |
| sw | 9131 | 17048 |
| swb | 672 | 800 |
| syc | 2855 | 20456 |
| szl | 237 | 386 |
| ta | 9064 | 11125 |
| te | 18707 | 41847 |
| tg | 2937 | 4995 |
| th | 94281 | 155060 |
| tk | 815 | 1560 |
| tpi | 1511 | 4032 |
| tpw | 270 | 540 |
| tr | 38490 | 71535 |
| tt | 4676 | 6086 |
| ty | 293 | 646 |
| tyv | 337 | 761 |
| ug | 998 | 2151 |
| uk | 27682 | 35275 |
| ur | 8476 | 17376 |
| uz | 5224 | 6296 |
| vec | 5555 | 11298 |
| vep | 2867 | 6443 |
| vi | 37433 | 105546 |
| vo | 8277 | 15818 |
| vot | 489 | 941 |
| wa | 1956 | 3189 |
| wau | 184 | 728 |
| wo | 1196 | 1855 |
| wym | 1330 | 2775 |
| xcl | 16182 | 40937 |
| yi | 8054 | 17814 |
| yua | 735 | 1571 |
| za | 473 | 1611 |
| zh | 274080 | 1040323 |
| zza | 621 | 1299 |
| abe | 185 | 353 |
| ady | 3807 | 8277 |
| ain | 298 | 555 |
| akk | 313 | 729 |
| akz | 151 | 271 |
| alt | 289 | 568 |
| an | 4457 | 5283 |
| axm | 350 | 828 |
| ccc | 445 | 619 |
| ch | 174 | 340 |
| chl | 528 | 905 |
| cho | 155 | 406 |
| chr | 1087 | 1560 |
| cic | 699 | 1128 |
| cjs | 306 | 512 |
| cv | 2892 | 3646 |
| dlm | 1091 | 4297 |
| dum | 2040 | 7426 |
| esu | 227 | 612 |
| ff | 215 | 404 |
| gmh | 217 | 620 |
| gn | 131 | 184 |
| goh | 2002 | 6720 |
| gsw | 2336 | 8129 |
| ha | 802 | 1743 |
| hit | 221 | 696 |
| ie | 637 | 840 |
| ii | 51 | 142 |
| ilo | 442 | 780 |
| jv | 4919 | 5949 |
| kbd | 762 | 1709 |
| kn | 3415 | 5158 |
| krl | 637 | 1033 |
| liv | 569 | 1630 |
| lkt | 682 | 1710 |
| ltg | 139 | 374 |
| lzz | 127 | 263 |
| mch | 384 | 582 |
| mh | 200 | 524 |
| ml | 6750 | 7108 |
| mr | 5545 | 9198 |
| na | 200 | 362 |
| nah | 1612 | 1627 |
| nan | 486 | 960 |
| ne | 4224 | 5605 |
| nhn | 269 | 499 |
| nmn | 313 | 998 |
| odt | 365 | 667 |
| ofs | 345 | 501 |
| oj | 587 | 1372 |
| or | 109 | 262 |
| orv | 199 | 374 |
| os | 4481 | 5616 |
| osx | 1848 | 4978 |
| pa | 4488 | 6511 |
| pap | 3612 | 9452 |
| peo | 184 | 566 |
| pms | 2857 | 3013 |
| qu | 5156 | 10936 |
| raj | 190 | 627 |
| rap | 313 | 618 |
| sah | 2695 | 3753 |
| sc | 573 | 1246 |
| sd | 143 | 334 |
| si | 2062 | 2248 |
| smn | 511 | 892 |
| sms | 493 | 771 |
| srn | 1249 | 3578 |
| sux | 785 | 1503 |
| tet | 361 | 658 |
| twf | 527 | 1291 |
| txb | 588 | 1344 |
| uga | 573 | 1382 |
| war | 12987 | 13825 |
| xh | 2504 | 3213 |
| xmf | 149 | 383 |
| xpr | 98 | 196 |
| xwo | 456 | 896 |
| yo | 2283 | 2384 |
| zu | 2758 | 8067 |
| co | 1474 | 2319 |
| prg | 480 | 913 |
| aii | 345 | 459 |
| am | 1909 | 2273 |
| bi | 92 | 320 |
| dv | 117 | 221 |
| kim | 388 | 473 |
| krc | 460 | 762 |
| kum | 505 | 871 |
| ti | 292 | 390 |
| udm | 306 | 436 |
| xto | 121 | 492 |
| zdj | 58 | 77 |
| dak | 879 | 1735 |
| frk | 1 | 8 |
| oma | 748 | 1111 |
| shh | 185 | 385 |
| aa | 725 | 987 |
| dje | 338 | 651 |
| hke | 246 | 514 |
| qya | 180 | 894 |
| st | 102 | 126 |
| wae | 437 | 566 |
| xno | 274 | 446 |
| dua | 317 | 834 |
| fon | 805 | 1858 |
| hak | 4 | 6 |
| jbo | 32 | 44 |
Licensing Information
This work includes data from ConceptNet 5, which was compiled by the Commonsense Computing Initiative. ConceptNet 5 is freely available under the Creative Commons Attribution-ShareAlike license (CC BY SA 3.0) from http://conceptnet.io.
Citation Information
@paper{speer2017conceptnet,
author = {Robyn Speer and Joshua Chin and Catherine Havasi},
title = {ConceptNet 5.5: An Open Multilingual Graph of General Knowledge},
conference = {AAAI Conference on Artificial Intelligence},
year = {2017},
pages = {4444--4451},
keywords = {ConceptNet; knowledge graph; word embeddings},
url = {http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14972}
}
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