Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
Chinese
Size:
< 1K
License:
| annotations_creators: | |
| - expert-generated | |
| language_creators: | |
| - found | |
| language: | |
| - zh | |
| license: | |
| - unknown | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 1K<n<10K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - token-classification | |
| task_ids: | |
| - named-entity-recognition | |
| paperswithcode_id: nlp-model-tune | |
| pretty_name: NER Model Tune | |
| train-eval-index: | |
| - config: default | |
| task: token-classification | |
| task_id: entity_extraction | |
| splits: | |
| train_split: train | |
| eval_split: test | |
| col_mapping: | |
| tokens: tokens | |
| ner_tags: tags | |
| metrics: | |
| - type: seqeval | |
| name: seqeval | |
| dataset_info: | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: tokens | |
| sequence: string | |
| - name: ner_tags | |
| sequence: | |
| class_label: | |
| names: | |
| '0': O, | |
| '1': B-CARDINAL, | |
| '2': B-DATE, | |
| '3': B-EVENT, | |
| '4': B-FAC, | |
| '5': B-GPE, | |
| '6': B-LANGUAGE, | |
| '7': B-LAW, | |
| '8': B-LOC, | |
| '9': B-MONEY, | |
| '10': B-NORP, | |
| '11': B-ORDINAL, | |
| '12': B-ORG, | |
| '13': B-PERCENT, | |
| '14': B-PERSON, | |
| '15': B-PRODUCT, | |
| '16': B-QUANTITY, | |
| '17': B-TIME, | |
| '18': B-WORK_OF_ART, | |
| '19': I-CARDINAL, | |
| '20': I-DATE, | |
| '21': I-EVENT, | |
| '22': I-FAC, | |
| '23': I-GPE, | |
| '24': I-LANGUAGE, | |
| '25': I-LAW, | |
| '26': I-LOC, | |
| '27': I-MONEY, | |
| '28': I-NORP, | |
| '29': I-ORDINAL, | |
| '30': I-ORG, | |
| '31': I-PERCENT, | |
| '32': I-PERSON, | |
| '33': I-PRODUCT, | |
| '34': I-QUANTITY, | |
| '35': I-TIME, | |
| '36': I-WORK_OF_ART, | |
| '37': E-CARDINAL, | |
| '38': E-DATE, | |
| '39': E-EVENT, | |
| '40': E-FAC, | |
| '41': E-GPE, | |
| '42': E-LANGUAGE, | |
| '43': E-LAW, | |
| '44': E-LOC, | |
| '45': E-MONEY, | |
| '46': E-NORP, | |
| '47': E-ORDINAL, | |
| '48': E-ORG, | |
| '49': E-PERCENT, | |
| '50': E-PERSON, | |
| '51': E-PRODUCT, | |
| '52': E-QUANTITY, | |
| '53': E-TIME, | |
| '54': E-WORK_OF_ART, | |
| '55': S-CARDINAL, | |
| '56': S-DATE, | |
| '57': S-EVENT, | |
| '58': S-FAC, | |
| '59': S-GPE, | |
| '60': S-LANGUAGE, | |
| '61': S-LAW, | |
| '62': S-LOC, | |
| '63': S-MONEY, | |
| '64': S-NORP, | |
| '65': S-ORDINAL, | |
| '66': S-ORG, | |
| '67': S-PERCENT, | |
| '68': S-PERSON, | |
| '69': S-PRODUCT, | |
| '70': S-QUANTITY, | |
| '71': S-TIME, | |
| '72': S-WORK_OF_ART | |
| splits: | |
| - name: train | |
| num_bytes: 568 | |
| num_examples: 1 | |
| download_size: 568 | |
| dataset_size: 568 | |
| # Dataset Card for "NER Model Tune" | |
| ## 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:** None | |
| - **Repository:** https://huggingface.co/datasets/ayuhamaro/nlp-model-tune | |
| - **Paper:** [More Information Needed] | |
| - **Leaderboard:** [If the dataset supports an active leaderboard, add link here]() | |
| - **Point of Contact:** [More Information Needed] | |
| ### Dataset Summary | |
| [More Information Needed] | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed] | |
| ### Languages | |
| [More Information Needed] | |
| ## Dataset Structure | |
| ### Data Instances | |
| [More Information Needed] | |
| ### Data Fields | |
| [More Information Needed] | |
| ### Data Splits | |
| [More Information Needed] | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed] | |
| ### Source Data | |
| [More Information Needed] | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| [More Information Needed] | |
| #### 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 | |
| [More Information Needed] | |
| ### Contributions |