| | --- |
| | annotations_creators: |
| | - expert-generated |
| | language_creators: |
| | - found |
| | language: |
| | - ar |
| | - en |
| | - zh |
| | license: |
| | - cc-by-nc-nd-4.0 |
| | multilinguality: |
| | - multilingual |
| | size_categories: |
| | - 10K<n<100K |
| | source_datasets: |
| | - original |
| | task_categories: |
| | - token-classification |
| | task_ids: |
| | - named-entity-recognition |
| | - part-of-speech |
| | - coreference-resolution |
| | - parsing |
| | - lemmatization |
| | - word-sense-disambiguation |
| | paperswithcode_id: ontonotes-5-0 |
| | pretty_name: CoNLL2012 shared task data based on OntoNotes 5.0 |
| | tags: |
| | - semantic-role-labeling |
| | dataset_info: |
| | - config_name: english_v4 |
| | features: |
| | - name: document_id |
| | dtype: string |
| | - name: sentences |
| | list: |
| | - name: part_id |
| | dtype: int32 |
| | - name: words |
| | sequence: string |
| | - name: pos_tags |
| | sequence: |
| | class_label: |
| | names: |
| | '0': XX |
| | '1': '``' |
| | '2': $ |
| | '3': '''''' |
| | '4': ',' |
| | '5': -LRB- |
| | '6': -RRB- |
| | '7': . |
| | '8': ':' |
| | '9': ADD |
| | '10': AFX |
| | '11': CC |
| | '12': CD |
| | '13': DT |
| | '14': EX |
| | '15': FW |
| | '16': HYPH |
| | '17': IN |
| | '18': JJ |
| | '19': JJR |
| | '20': JJS |
| | '21': LS |
| | '22': MD |
| | '23': NFP |
| | '24': NN |
| | '25': NNP |
| | '26': NNPS |
| | '27': NNS |
| | '28': PDT |
| | '29': POS |
| | '30': PRP |
| | '31': PRP$ |
| | '32': RB |
| | '33': RBR |
| | '34': RBS |
| | '35': RP |
| | '36': SYM |
| | '37': TO |
| | '38': UH |
| | '39': VB |
| | '40': VBD |
| | '41': VBG |
| | '42': VBN |
| | '43': VBP |
| | '44': VBZ |
| | '45': WDT |
| | '46': WP |
| | '47': WP$ |
| | '48': WRB |
| | - name: parse_tree |
| | dtype: string |
| | - name: predicate_lemmas |
| | sequence: string |
| | - name: predicate_framenet_ids |
| | sequence: string |
| | - name: word_senses |
| | sequence: float32 |
| | - name: speaker |
| | dtype: string |
| | - name: named_entities |
| | sequence: |
| | class_label: |
| | names: |
| | '0': O |
| | '1': B-PERSON |
| | '2': I-PERSON |
| | '3': B-NORP |
| | '4': I-NORP |
| | '5': B-FAC |
| | '6': I-FAC |
| | '7': B-ORG |
| | '8': I-ORG |
| | '9': B-GPE |
| | '10': I-GPE |
| | '11': B-LOC |
| | '12': I-LOC |
| | '13': B-PRODUCT |
| | '14': I-PRODUCT |
| | '15': B-DATE |
| | '16': I-DATE |
| | '17': B-TIME |
| | '18': I-TIME |
| | '19': B-PERCENT |
| | '20': I-PERCENT |
| | '21': B-MONEY |
| | '22': I-MONEY |
| | '23': B-QUANTITY |
| | '24': I-QUANTITY |
| | '25': B-ORDINAL |
| | '26': I-ORDINAL |
| | '27': B-CARDINAL |
| | '28': I-CARDINAL |
| | '29': B-EVENT |
| | '30': I-EVENT |
| | '31': B-WORK_OF_ART |
| | '32': I-WORK_OF_ART |
| | '33': B-LAW |
| | '34': I-LAW |
| | '35': B-LANGUAGE |
| | '36': I-LANGUAGE |
| | - name: srl_frames |
| | list: |
| | - name: verb |
| | dtype: string |
| | - name: frames |
| | sequence: string |
| | - name: coref_spans |
| | sequence: |
| | sequence: int32 |
| | length: 3 |
| | splits: |
| | - name: train |
| | num_bytes: 112246121 |
| | num_examples: 1940 |
| | - name: validation |
| | num_bytes: 14116925 |
| | num_examples: 222 |
| | - name: test |
| | num_bytes: 14709044 |
| | num_examples: 222 |
| | download_size: 193644139 |
| | dataset_size: 141072090 |
| | - config_name: chinese_v4 |
| | features: |
| | - name: document_id |
| | dtype: string |
| | - name: sentences |
| | list: |
| | - name: part_id |
| | dtype: int32 |
| | - name: words |
| | sequence: string |
| | - name: pos_tags |
| | sequence: |
| | class_label: |
| | names: |
| | '0': X |
| | '1': AD |
| | '2': AS |
| | '3': BA |
| | '4': CC |
| | '5': CD |
| | '6': CS |
| | '7': DEC |
| | '8': DEG |
| | '9': DER |
| | '10': DEV |
| | '11': DT |
| | '12': ETC |
| | '13': FW |
| | '14': IJ |
| | '15': INF |
| | '16': JJ |
| | '17': LB |
| | '18': LC |
| | '19': M |
| | '20': MSP |
| | '21': NN |
| | '22': NR |
| | '23': NT |
| | '24': OD |
| | '25': 'ON' |
| | '26': P |
| | '27': PN |
| | '28': PU |
| | '29': SB |
| | '30': SP |
| | '31': URL |
| | '32': VA |
| | '33': VC |
| | '34': VE |
| | '35': VV |
| | - name: parse_tree |
| | dtype: string |
| | - name: predicate_lemmas |
| | sequence: string |
| | - name: predicate_framenet_ids |
| | sequence: string |
| | - name: word_senses |
| | sequence: float32 |
| | - name: speaker |
| | dtype: string |
| | - name: named_entities |
| | sequence: |
| | class_label: |
| | names: |
| | '0': O |
| | '1': B-PERSON |
| | '2': I-PERSON |
| | '3': B-NORP |
| | '4': I-NORP |
| | '5': B-FAC |
| | '6': I-FAC |
| | '7': B-ORG |
| | '8': I-ORG |
| | '9': B-GPE |
| | '10': I-GPE |
| | '11': B-LOC |
| | '12': I-LOC |
| | '13': B-PRODUCT |
| | '14': I-PRODUCT |
| | '15': B-DATE |
| | '16': I-DATE |
| | '17': B-TIME |
| | '18': I-TIME |
| | '19': B-PERCENT |
| | '20': I-PERCENT |
| | '21': B-MONEY |
| | '22': I-MONEY |
| | '23': B-QUANTITY |
| | '24': I-QUANTITY |
| | '25': B-ORDINAL |
| | '26': I-ORDINAL |
| | '27': B-CARDINAL |
| | '28': I-CARDINAL |
| | '29': B-EVENT |
| | '30': I-EVENT |
| | '31': B-WORK_OF_ART |
| | '32': I-WORK_OF_ART |
| | '33': B-LAW |
| | '34': I-LAW |
| | '35': B-LANGUAGE |
| | '36': I-LANGUAGE |
| | - name: srl_frames |
| | list: |
| | - name: verb |
| | dtype: string |
| | - name: frames |
| | sequence: string |
| | - name: coref_spans |
| | sequence: |
| | sequence: int32 |
| | length: 3 |
| | splits: |
| | - name: train |
| | num_bytes: 77195698 |
| | num_examples: 1391 |
| | - name: validation |
| | num_bytes: 10828169 |
| | num_examples: 172 |
| | - name: test |
| | num_bytes: 9585138 |
| | num_examples: 166 |
| | download_size: 193644139 |
| | dataset_size: 97609005 |
| | - config_name: arabic_v4 |
| | features: |
| | - name: document_id |
| | dtype: string |
| | - name: sentences |
| | list: |
| | - name: part_id |
| | dtype: int32 |
| | - name: words |
| | sequence: string |
| | - name: pos_tags |
| | sequence: string |
| | - name: parse_tree |
| | dtype: string |
| | - name: predicate_lemmas |
| | sequence: string |
| | - name: predicate_framenet_ids |
| | sequence: string |
| | - name: word_senses |
| | sequence: float32 |
| | - name: speaker |
| | dtype: string |
| | - name: named_entities |
| | sequence: |
| | class_label: |
| | names: |
| | '0': O |
| | '1': B-PERSON |
| | '2': I-PERSON |
| | '3': B-NORP |
| | '4': I-NORP |
| | '5': B-FAC |
| | '6': I-FAC |
| | '7': B-ORG |
| | '8': I-ORG |
| | '9': B-GPE |
| | '10': I-GPE |
| | '11': B-LOC |
| | '12': I-LOC |
| | '13': B-PRODUCT |
| | '14': I-PRODUCT |
| | '15': B-DATE |
| | '16': I-DATE |
| | '17': B-TIME |
| | '18': I-TIME |
| | '19': B-PERCENT |
| | '20': I-PERCENT |
| | '21': B-MONEY |
| | '22': I-MONEY |
| | '23': B-QUANTITY |
| | '24': I-QUANTITY |
| | '25': B-ORDINAL |
| | '26': I-ORDINAL |
| | '27': B-CARDINAL |
| | '28': I-CARDINAL |
| | '29': B-EVENT |
| | '30': I-EVENT |
| | '31': B-WORK_OF_ART |
| | '32': I-WORK_OF_ART |
| | '33': B-LAW |
| | '34': I-LAW |
| | '35': B-LANGUAGE |
| | '36': I-LANGUAGE |
| | - name: srl_frames |
| | list: |
| | - name: verb |
| | dtype: string |
| | - name: frames |
| | sequence: string |
| | - name: coref_spans |
| | sequence: |
| | sequence: int32 |
| | length: 3 |
| | splits: |
| | - name: train |
| | num_bytes: 42017761 |
| | num_examples: 359 |
| | - name: validation |
| | num_bytes: 4859292 |
| | num_examples: 44 |
| | - name: test |
| | num_bytes: 4900664 |
| | num_examples: 44 |
| | download_size: 193644139 |
| | dataset_size: 51777717 |
| | - config_name: english_v12 |
| | features: |
| | - name: document_id |
| | dtype: string |
| | - name: sentences |
| | list: |
| | - name: part_id |
| | dtype: int32 |
| | - name: words |
| | sequence: string |
| | - name: pos_tags |
| | sequence: |
| | class_label: |
| | names: |
| | '0': XX |
| | '1': '``' |
| | '2': $ |
| | '3': '''''' |
| | '4': '*' |
| | '5': ',' |
| | '6': -LRB- |
| | '7': -RRB- |
| | '8': . |
| | '9': ':' |
| | '10': ADD |
| | '11': AFX |
| | '12': CC |
| | '13': CD |
| | '14': DT |
| | '15': EX |
| | '16': FW |
| | '17': HYPH |
| | '18': IN |
| | '19': JJ |
| | '20': JJR |
| | '21': JJS |
| | '22': LS |
| | '23': MD |
| | '24': NFP |
| | '25': NN |
| | '26': NNP |
| | '27': NNPS |
| | '28': NNS |
| | '29': PDT |
| | '30': POS |
| | '31': PRP |
| | '32': PRP$ |
| | '33': RB |
| | '34': RBR |
| | '35': RBS |
| | '36': RP |
| | '37': SYM |
| | '38': TO |
| | '39': UH |
| | '40': VB |
| | '41': VBD |
| | '42': VBG |
| | '43': VBN |
| | '44': VBP |
| | '45': VBZ |
| | '46': VERB |
| | '47': WDT |
| | '48': WP |
| | '49': WP$ |
| | '50': WRB |
| | - name: parse_tree |
| | dtype: string |
| | - name: predicate_lemmas |
| | sequence: string |
| | - name: predicate_framenet_ids |
| | sequence: string |
| | - name: word_senses |
| | sequence: float32 |
| | - name: speaker |
| | dtype: string |
| | - name: named_entities |
| | sequence: |
| | class_label: |
| | names: |
| | '0': O |
| | '1': B-PERSON |
| | '2': I-PERSON |
| | '3': B-NORP |
| | '4': I-NORP |
| | '5': B-FAC |
| | '6': I-FAC |
| | '7': B-ORG |
| | '8': I-ORG |
| | '9': B-GPE |
| | '10': I-GPE |
| | '11': B-LOC |
| | '12': I-LOC |
| | '13': B-PRODUCT |
| | '14': I-PRODUCT |
| | '15': B-DATE |
| | '16': I-DATE |
| | '17': B-TIME |
| | '18': I-TIME |
| | '19': B-PERCENT |
| | '20': I-PERCENT |
| | '21': B-MONEY |
| | '22': I-MONEY |
| | '23': B-QUANTITY |
| | '24': I-QUANTITY |
| | '25': B-ORDINAL |
| | '26': I-ORDINAL |
| | '27': B-CARDINAL |
| | '28': I-CARDINAL |
| | '29': B-EVENT |
| | '30': I-EVENT |
| | '31': B-WORK_OF_ART |
| | '32': I-WORK_OF_ART |
| | '33': B-LAW |
| | '34': I-LAW |
| | '35': B-LANGUAGE |
| | '36': I-LANGUAGE |
| | - name: srl_frames |
| | list: |
| | - name: verb |
| | dtype: string |
| | - name: frames |
| | sequence: string |
| | - name: coref_spans |
| | sequence: |
| | sequence: int32 |
| | length: 3 |
| | splits: |
| | - name: train |
| | num_bytes: 174173192 |
| | num_examples: 10539 |
| | - name: validation |
| | num_bytes: 24264804 |
| | num_examples: 1370 |
| | - name: test |
| | num_bytes: 18254144 |
| | num_examples: 1200 |
| | download_size: 193644139 |
| | dataset_size: 216692140 |
| | --- |
| | |
| | # Dataset Card for CoNLL2012 shared task data based on OntoNotes 5.0 |
| |
|
| | ## Table of Contents |
| | - [Table of Contents](#table-of-contents) |
| | - [Dataset Description](#dataset-description) |
| | - [Dataset Summary](#dataset-summary) |
| | - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| | - [Languages](#languages) |
| | - [Dataset Structure](#dataset-structure) |
| | - [Data Instances](#data-instances) |
| | - [Data Fields](#data-fields) |
| | - [Data Splits](#data-splits) |
| | - [Dataset Creation](#dataset-creation) |
| | - [Curation Rationale](#curation-rationale) |
| | - [Source Data](#source-data) |
| | - [Annotations](#annotations) |
| | - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| | - [Considerations for Using the Data](#considerations-for-using-the-data) |
| | - [Social Impact of Dataset](#social-impact-of-dataset) |
| | - [Discussion of Biases](#discussion-of-biases) |
| | - [Other Known Limitations](#other-known-limitations) |
| | - [Additional Information](#additional-information) |
| | - [Dataset Curators](#dataset-curators) |
| | - [Licensing Information](#licensing-information) |
| | - [Citation Information](#citation-information) |
| | - [Contributions](#contributions) |
| |
|
| | ## Dataset Description |
| |
|
| | - **Homepage:** [CoNLL-2012 Shared Task](https://conll.cemantix.org/2012/data.html), [Author's page](https://cemantix.org/data/ontonotes.html) |
| | - **Repository:** [Mendeley](https://data.mendeley.com/datasets/zmycy7t9h9) |
| | - **Paper:** [Towards Robust Linguistic Analysis using OntoNotes](https://aclanthology.org/W13-3516/) |
| | - **Leaderboard:** |
| | - **Point of Contact:** |
| |
|
| | ### Dataset Summary |
| |
|
| | OntoNotes v5.0 is the final version of OntoNotes corpus, and is a large-scale, multi-genre, |
| | multilingual corpus manually annotated with syntactic, semantic and discourse information. |
| |
|
| | This dataset is the version of OntoNotes v5.0 extended and is used in the CoNLL-2012 shared task. |
| | It includes v4 train/dev and v9 test data for English/Chinese/Arabic and corrected version v12 train/dev/test data (English only). |
| |
|
| | The source of data is the Mendeley Data repo [ontonotes-conll2012](https://data.mendeley.com/datasets/zmycy7t9h9), which seems to be as the same as the official data, but users should use this dataset on their own responsibility. |
| |
|
| | See also summaries from paperwithcode, [OntoNotes 5.0](https://paperswithcode.com/dataset/ontonotes-5-0) and [CoNLL-2012](https://paperswithcode.com/dataset/conll-2012-1) |
| |
|
| | For more detailed info of the dataset like annotation, tag set, etc., you can refer to the documents in the Mendeley repo mentioned above. |
| |
|
| | ### Supported Tasks and Leaderboards |
| |
|
| | - [Named Entity Recognition on Ontonotes v5 (English)](https://paperswithcode.com/sota/named-entity-recognition-ner-on-ontonotes-v5) |
| | - [Coreference Resolution on OntoNotes](https://paperswithcode.com/sota/coreference-resolution-on-ontonotes) |
| | - [Semantic Role Labeling on OntoNotes](https://paperswithcode.com/sota/semantic-role-labeling-on-ontonotes) |
| | - ... |
| |
|
| | ### Languages |
| |
|
| | V4 data for Arabic, Chinese, English, and V12 data for English |
| |
|
| | ## Dataset Structure |
| |
|
| | ### Data Instances |
| |
|
| | ``` |
| | { |
| | {'document_id': 'nw/wsj/23/wsj_2311', |
| | 'sentences': [{'part_id': 0, |
| | 'words': ['CONCORDE', 'trans-Atlantic', 'flights', 'are', '$', '2, 'to', 'Paris', 'and', '$', '3, 'to', 'London', '.']}, |
| | 'pos_tags': [25, 18, 27, 43, 2, 12, 17, 25, 11, 2, 12, 17, 25, 7], |
| | 'parse_tree': '(TOP(S(NP (NNP CONCORDE) (JJ trans-Atlantic) (NNS flights) )(VP (VBP are) (NP(NP(NP ($ $) (CD 2,400) )(PP (IN to) (NP (NNP Paris) ))) (CC and) (NP(NP ($ $) (CD 3,200) )(PP (IN to) (NP (NNP London) ))))) (. .) ))', |
| | 'predicate_lemmas': [None, None, None, 'be', None, None, None, None, None, None, None, None, None, None], |
| | 'predicate_framenet_ids': [None, None, None, '01', None, None, None, None, None, None, None, None, None, None], |
| | 'word_senses': [None, None, None, None, None, None, None, None, None, None, None, None, None, None], |
| | 'speaker': None, |
| | 'named_entities': [7, 6, 0, 0, 0, 15, 0, 5, 0, 0, 15, 0, 5, 0], |
| | 'srl_frames': [{'frames': ['B-ARG1', 'I-ARG1', 'I-ARG1', 'B-V', 'B-ARG2', 'I-ARG2', 'I-ARG2', 'I-ARG2', 'I-ARG2', 'I-ARG2', 'I-ARG2', 'I-ARG2', 'I-ARG2', 'O'], |
| | 'verb': 'are'}], |
| | 'coref_spans': [], |
| | {'part_id': 0, |
| | 'words': ['In', 'a', 'Centennial', 'Journal', 'article', 'Oct.', '5', ',', 'the', 'fares', 'were', 'reversed', '.']}]} |
| | 'pos_tags': [17, 13, 25, 25, 24, 25, 12, 4, 13, 27, 40, 42, 7], |
| | 'parse_tree': '(TOP(S(PP (IN In) (NP (DT a) (NML (NNP Centennial) (NNP Journal) ) (NN article) ))(NP (NNP Oct.) (CD 5) ) (, ,) (NP (DT the) (NNS fares) )(VP (VBD were) (VP (VBN reversed) )) (. .) ))', |
| | 'predicate_lemmas': [None, None, None, None, None, None, None, None, None, None, None, 'reverse', None], |
| | 'predicate_framenet_ids': [None, None, None, None, None, None, None, None, None, None, None, '01', None], |
| | 'word_senses': [None, None, None, None, None, None, None, None, None, None, None, None, None], |
| | 'speaker': None, |
| | 'named_entities': [0, 0, 4, 22, 0, 12, 30, 0, 0, 0, 0, 0, 0], |
| | 'srl_frames': [{'frames': ['B-ARGM-LOC', 'I-ARGM-LOC', 'I-ARGM-LOC', 'I-ARGM-LOC', 'I-ARGM-LOC', 'B-ARGM-TMP', 'I-ARGM-TMP', 'O', 'B-ARG1', 'I-ARG1', 'O', 'B-V', 'O'], |
| | 'verb': 'reversed'}], |
| | 'coref_spans': [], |
| | } |
| | ``` |
| |
|
| | ### Data Fields |
| |
|
| | - **`document_id`** (*`str`*): This is a variation on the document filename |
| | - **`sentences`** (*`List[Dict]`*): All sentences of the same document are in a single example for the convenience of concatenating sentences. |
| | |
| | Every element in `sentences` is a *`Dict`* composed of the following data fields: |
| | - **`part_id`** (*`int`*) : Some files are divided into multiple parts numbered as 000, 001, 002, ... etc. |
| | - **`words`** (*`List[str]`*) : |
| | - **`pos_tags`** (*`List[ClassLabel]` or `List[str]`*) : This is the Penn-Treebank-style part of speech. When parse information is missing, all parts of speech except the one for which there is some sense or proposition annotation are marked with a XX tag. The verb is marked with just a VERB tag. |
| | - tag set : Note tag sets below are founded by scanning all the data, and I found it seems to be a little bit different from officially stated tag sets. See official documents in the [Mendeley repo](https://data.mendeley.com/datasets/zmycy7t9h9) |
| | - arabic : str. Because pos tag in Arabic is compounded and complex, hard to represent it by `ClassLabel` |
| | - chinese v4 : `datasets.ClassLabel(num_classes=36, names=["X", "AD", "AS", "BA", "CC", "CD", "CS", "DEC", "DEG", "DER", "DEV", "DT", "ETC", "FW", "IJ", "INF", "JJ", "LB", "LC", "M", "MSP", "NN", "NR", "NT", "OD", "ON", "P", "PN", "PU", "SB", "SP", "URL", "VA", "VC", "VE", "VV",])`, where `X` is for pos tag missing |
| | - english v4 : `datasets.ClassLabel(num_classes=49, names=["XX", "``", "$", "''", ",", "-LRB-", "-RRB-", ".", ":", "ADD", "AFX", "CC", "CD", "DT", "EX", "FW", "HYPH", "IN", "JJ", "JJR", "JJS", "LS", "MD", "NFP", "NN", "NNP", "NNPS", "NNS", "PDT", "POS", "PRP", "PRP$", "RB", "RBR", "RBS", "RP", "SYM", "TO", "UH", "VB", "VBD", "VBG", "VBN", "VBP", "VBZ", "WDT", "WP", "WP$", "WRB",])`, where `XX` is for pos tag missing, and `-LRB-`/`-RRB-` is "`(`" / "`)`". |
| | - english v12 : `datasets.ClassLabel(num_classes=51, names="english_v12": ["XX", "``", "$", "''", "*", ",", "-LRB-", "-RRB-", ".", ":", "ADD", "AFX", "CC", "CD", "DT", "EX", "FW", "HYPH", "IN", "JJ", "JJR", "JJS", "LS", "MD", "NFP", "NN", "NNP", "NNPS", "NNS", "PDT", "POS", "PRP", "PRP$", "RB", "RBR", "RBS", "RP", "SYM", "TO", "UH", "VB", "VBD", "VBG", "VBN", "VBP", "VBZ", "VERB", "WDT", "WP", "WP$", "WRB",])`, where `XX` is for pos tag missing, and `-LRB-`/`-RRB-` is "`(`" / "`)`". |
| | - **`parse_tree`** (*`Optional[str]`*) : An serialized NLTK Tree representing the parse. It includes POS tags as pre-terminal nodes. When the parse information is missing, the parse will be `None`. |
| | - **`predicate_lemmas`** (*`List[Optional[str]]`*) : The predicate lemma of the words for which we have semantic role information or word sense information. All other indices are `None`. |
| | - **`predicate_framenet_ids`** (*`List[Optional[int]]`*) : The PropBank frameset ID of the lemmas in predicate_lemmas, or `None`. |
| | - **`word_senses`** (*`List[Optional[float]]`*) : The word senses for the words in the sentence, or None. These are floats because the word sense can have values after the decimal, like 1.1. |
| | - **`speaker`** (*`Optional[str]`*) : This is the speaker or author name where available. Mostly in Broadcast Conversation and Web Log data. When it is not available, it will be `None`. |
| | - **`named_entities`** (*`List[ClassLabel]`*) : The BIO tags for named entities in the sentence. |
| | - tag set : `datasets.ClassLabel(num_classes=37, names=["O", "B-PERSON", "I-PERSON", "B-NORP", "I-NORP", "B-FAC", "I-FAC", "B-ORG", "I-ORG", "B-GPE", "I-GPE", "B-LOC", "I-LOC", "B-PRODUCT", "I-PRODUCT", "B-DATE", "I-DATE", "B-TIME", "I-TIME", "B-PERCENT", "I-PERCENT", "B-MONEY", "I-MONEY", "B-QUANTITY", "I-QUANTITY", "B-ORDINAL", "I-ORDINAL", "B-CARDINAL", "I-CARDINAL", "B-EVENT", "I-EVENT", "B-WORK_OF_ART", "I-WORK_OF_ART", "B-LAW", "I-LAW", "B-LANGUAGE", "I-LANGUAGE",])` |
| | - **`srl_frames`** (*`List[{"word":str, "frames":List[str]}]`*) : A dictionary keyed by the verb in the sentence for the given Propbank frame labels, in a BIO format. |
| | - **`coref spans`** (*`List[List[int]]`*) : The spans for entity mentions involved in coreference resolution within the sentence. Each element is a tuple composed of (cluster_id, start_index, end_index). Indices are inclusive. |
| | |
| | ### Data Splits |
| | |
| | Each dataset (arabic_v4, chinese_v4, english_v4, english_v12) has 3 splits: _train_, _validation_, and _test_ |
| |
|
| | ## Dataset Creation |
| |
|
| | ### Curation Rationale |
| |
|
| | [More Information Needed] |
| |
|
| | ### Source Data |
| |
|
| | #### Initial Data Collection and Normalization |
| |
|
| | [More Information Needed] |
| |
|
| | #### Who are the source language producers? |
| |
|
| | [More Information Needed] |
| |
|
| | ### Annotations |
| |
|
| | #### Annotation process |
| |
|
| | [More Information Needed] |
| |
|
| | #### Who are the annotators? |
| |
|
| | [More Information Needed] |
| |
|
| | ### Personal and Sensitive Information |
| |
|
| | [More Information Needed] |
| |
|
| | ## Considerations for Using the Data |
| |
|
| | ### Social Impact of Dataset |
| |
|
| | [More Information Needed] |
| |
|
| | ### Discussion of Biases |
| |
|
| | [More Information Needed] |
| |
|
| | ### Other Known Limitations |
| |
|
| | [More Information Needed] |
| |
|
| | ## Additional Information |
| |
|
| | ### Dataset Curators |
| |
|
| | [More Information Needed] |
| |
|
| | ### Licensing Information |
| |
|
| | [More Information Needed] |
| |
|
| | ### Citation Information |
| |
|
| | ``` |
| | @inproceedings{pradhan-etal-2013-towards, |
| | title = "Towards Robust Linguistic Analysis using {O}nto{N}otes", |
| | author = {Pradhan, Sameer and |
| | Moschitti, Alessandro and |
| | Xue, Nianwen and |
| | Ng, Hwee Tou and |
| | Bj{\"o}rkelund, Anders and |
| | Uryupina, Olga and |
| | Zhang, Yuchen and |
| | Zhong, Zhi}, |
| | booktitle = "Proceedings of the Seventeenth Conference on Computational Natural Language Learning", |
| | month = aug, |
| | year = "2013", |
| | address = "Sofia, Bulgaria", |
| | publisher = "Association for Computational Linguistics", |
| | url = "https://aclanthology.org/W13-3516", |
| | pages = "143--152", |
| | } |
| | ``` |
| |
|
| | ### Contributions |
| |
|
| | Thanks to [@richarddwang](https://github.com/richarddwang) for adding this dataset. |
