Sentence # stringlengths 11 15 ⌀ | Word stringlengths 1 64 ⌀ | POS stringclasses 42 values | Tag stringclasses 17 values |
|---|---|---|---|
Sentence: 1 | Thousands | NNS | O |
null | of | IN | O |
null | demonstrators | NNS | O |
null | have | VBP | O |
null | marched | VBN | O |
null | through | IN | O |
null | London | NNP | B-geo |
null | to | TO | O |
null | protest | VB | O |
null | the | DT | O |
null | war | NN | O |
null | in | IN | O |
null | Iraq | NNP | B-geo |
null | and | CC | O |
null | demand | VB | O |
null | the | DT | O |
null | withdrawal | NN | O |
null | of | IN | O |
null | British | JJ | B-gpe |
null | troops | NNS | O |
null | from | IN | O |
null | that | DT | O |
null | country | NN | O |
null | . | . | O |
Sentence: 2 | Families | NNS | O |
null | of | IN | O |
null | soldiers | NNS | O |
null | killed | VBN | O |
null | in | IN | O |
null | the | DT | O |
null | conflict | NN | O |
null | joined | VBD | O |
null | the | DT | O |
null | protesters | NNS | O |
null | who | WP | O |
null | carried | VBD | O |
null | banners | NNS | O |
null | with | IN | O |
null | such | JJ | O |
null | slogans | NNS | O |
null | as | IN | O |
null | null | `` | O |
null | Bush | NNP | B-per |
null | Number | NN | O |
null | One | CD | O |
null | Terrorist | NN | O |
null | null | `` | O |
null | and | CC | O |
null | null | `` | O |
null | Stop | VB | O |
null | the | DT | O |
null | Bombings | NNS | O |
null | . | . | O |
null | null | `` | O |
Sentence: 3 | They | PRP | O |
null | marched | VBD | O |
null | from | IN | O |
null | the | DT | O |
null | Houses | NNS | O |
null | of | IN | O |
null | Parliament | NN | O |
null | to | TO | O |
null | a | DT | O |
null | rally | NN | O |
null | in | IN | O |
null | Hyde | NNP | B-geo |
null | Park | NNP | I-geo |
null | . | . | O |
Sentence: 4 | Police | NNS | O |
null | put | VBD | O |
null | the | DT | O |
null | number | NN | O |
null | of | IN | O |
null | marchers | NNS | O |
null | at | IN | O |
null | 10,000 | CD | O |
null | while | IN | O |
null | organizers | NNS | O |
null | claimed | VBD | O |
null | it | PRP | O |
null | was | VBD | O |
null | 1,00,000 | CD | O |
null | . | . | O |
Sentence: 5 | The | DT | O |
null | protest | NN | O |
null | comes | VBZ | O |
null | on | IN | O |
null | the | DT | O |
null | eve | NN | O |
null | of | IN | O |
null | the | DT | O |
null | annual | JJ | O |
null | conference | NN | O |
null | of | IN | O |
null | Britain | NNP | B-geo |
null | 's | POS | O |
null | ruling | VBG | O |
null | Labor | NNP | B-org |
null | Party | NNP | I-org |
null | in | IN | O |
YAML Metadata Warning: The task_categories "Name Entity Recognisition" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
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