Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
License:
sentence
stringlengths 4
127
| accent
stringlengths 4
147
| input_features
sequence | labels
sequence |
---|---|---|---|
Men in orange vests are at work on a construction site. | India and South Asia (India, Pakistan, Sri Lanka) | [[-0.22105646133422852,-0.034386277198791504,-0.06598472595214844,0.46144479513168335,0.435927033424(...TRUNCATED) | [
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294,
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366,
412,
589,
322,
257,
6435,
3621,
13,
50257
] |
This child is getting a pedicure. | India and South Asia (India, Pakistan, Sri Lanka) | [[0.45610785484313965,0.3137545585632324,0.058347463607788086,-0.18743634223937988,-0.08052802085876(...TRUNCATED) | [
50258,
50259,
50359,
50363,
5723,
1440,
307,
1242,
257,
5670,
299,
540,
13,
50257
] |
Did you get the Mayor? | India and South Asia (India, Pakistan, Sri Lanka) | [[-0.6610622406005859,-0.3692203760147095,-0.5351134538650513,0.28412342071533203,-0.021078348159790(...TRUNCATED) | [
50258,
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50363,
17648,
291,
483,
220,
3322,
13925,
30,
50257
] |
Finally I didn't have to feel guilty for using my computer on weekends. | India and South Asia (India, Pakistan, Sri Lanka) | [[-0.6572308540344238,-0.15708136558532715,-0.1690976619720459,-0.3987048864364624,-0.07946288585662(...TRUNCATED) | [50258,50259,50359,50363,44259,286,994,380,362,220,1353,841,12341,337,1228,452,3820,322,23595,13,502(...TRUNCATED) |
I'd still like to have a word with her. | India and South Asia (India, Pakistan, Sri Lanka) | [[-0.3918297290802002,-0.39190077781677246,-0.4548325538635254,-0.24374628067016602,-0.3293899297714(...TRUNCATED) | [
50258,
50259,
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40,
1116,
920,
411,
220,
1353,
362,
257,
1349,
365,
720,
13,
50257
] |
This view is wrong though. | India and South Asia (India, Pakistan, Sri Lanka) | [[-0.5115571022033691,-0.5115571022033691,0.6893160343170166,0.6999656558036804,0.607867419719696,0.(...TRUNCATED) | [
50258,
50259,
50359,
50363,
5723,
1910,
307,
2085,
220,
3222,
13,
50257
] |
Fedric was unable to find his lucky marble. | India and South Asia (India, Pakistan, Sri Lanka) | [[0.25525879859924316,-0.02833545207977295,0.047033727169036865,0.2693023681640625,0.146158456802368(...TRUNCATED) | [
50258,
50259,
50359,
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37,
292,
1341,
390,
11299,
220,
1353,
915,
702,
6356,
26844,
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50257
] |
Whistle-blower Edward Snowden still lives in exile in Russia. | India and South Asia (India, Pakistan, Sri Lanka) | [[-0.6399859189987183,-0.6399859189987183,-0.6399859189987183,-0.4123953580856323,-0.158420205116271(...TRUNCATED) | [50258,50259,50359,50363,2471,16088,12,5199,968,18456,14827,1556,920,2909,294,37984,294,6797,13,5025(...TRUNCATED) |
I work at the hospital as a paediatrician. | India and South Asia (India, Pakistan, Sri Lanka) | [[-0.4472612142562866,-0.3678094148635864,-0.27979421615600586,-0.05543673038482666,-0.1067335605621(...TRUNCATED) | [
50258,
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40,
589,
412,
220,
3322,
4530,
382,
257,
2502,
292,
17252,
952,
13,
50257
] |
The squirrel ran up the pine tree in a spiral. | India and South Asia (India, Pakistan, Sri Lanka) | [[-0.0866396427154541,-0.22658979892730713,-0.263979434967041,-0.1374194622039795,-0.344581842422485(...TRUNCATED) | [
50258,
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220,
3322,
15113,
220,
83,
701,
294,
257,
25165,
13,
50257
] |
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The task_ids "token-classification-other-acronym-identification" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering
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