README.md

metadata

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: ws-pos-model-tune
pretty_name: WS POS 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: ws_tags
      sequence:
        class_label:
          names:
            '0': B,
            '1': I
    - name: pos_tags
      sequence:
        class_label:
          names:
            '0': A,
            '1': Caa,
            '2': Cab,
            '3': Cba,
            '4': Cbb,
            '5': D,
            '6': Da,
            '7': Dfa,
            '8': Dfb,
            '9': Di,
            '10': Dk,
            '11': DM,
            '12': I,
            '13': Na,
            '14': Nb,
            '15': Nc,
            '16': Ncd,
            '17': Nd,
            '18': Nep,
            '19': Neqa,
            '20': Neqb,
            '21': Nes,
            '22': Neu,
            '23': Nf,
            '24': Ng,
            '25': Nh,
            '26': Nv,
            '27': P,
            '28': T,
            '29': VA,
            '30': VAC,
            '31': VB,
            '32': VC,
            '33': VCL,
            '34': VD,
            '35': VF,
            '36': VE,
            '37': VG,
            '38': VH,
            '39': VHC,
            '40': VI,
            '41': VJ,
            '42': VK,
            '43': VL,
            '44': V_2,
            '45': DE,
            '46': SHI,
            '47': FW,
            '48': COLONCATEGORY,
            '49': COMMACATEGORY,
            '50': DASHCATEGORY,
            '51': DOTCATEGORY,
            '52': ETCCATEGORY,
            '53': EXCLAMATIONCATEGORY,
            '54': PARENTHESISCATEGORY,
            '55': PAUSECATEGORY,
            '56': PERIODCATEGORY,
            '57': QUESTIONCATEGORY,
            '58': SEMICOLONCATEGORY,
            '59': SPCHANGECATEGORY
  splits:
    - name: train
      num_bytes: 1024
      num_examples: 1
  download_size: 1024
  dataset_size: 1024

Dataset Card for "WS POS Model Tune"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • 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