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conceptnet_all

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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 240, 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.

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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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