metadata

license: other
license_name: other
license_link: LICENSE
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: id
      dtype: string
    - name: tokens
      sequence: string
    - name: pos_tags
      sequence:
        class_label:
          names:
            '0': '"'
            '1': ''''''
            '2': '#'
            '3': $
            '4': (
            '5': )
            '6': ','
            '7': .
            '8': ':'
            '9': '``'
            '10': CC
            '11': CD
            '12': DT
            '13': EX
            '14': FW
            '15': IN
            '16': JJ
            '17': JJR
            '18': JJS
            '19': LS
            '20': MD
            '21': NN
            '22': NNP
            '23': NNPS
            '24': NNS
            '25': NN|SYM
            '26': PDT
            '27': POS
            '28': PRP
            '29': PRP$
            '30': RB
            '31': RBR
            '32': RBS
            '33': RP
            '34': SYM
            '35': TO
            '36': UH
            '37': VB
            '38': VBD
            '39': VBG
            '40': VBN
            '41': VBP
            '42': VBZ
            '43': WDT
            '44': WP
            '45': WP$
            '46': WRB
    - name: chunk_tags
      sequence:
        class_label:
          names:
            '0': O
            '1': B-ADJP
            '2': I-ADJP
            '3': B-ADVP
            '4': I-ADVP
            '5': B-CONJP
            '6': I-CONJP
            '7': B-INTJ
            '8': I-INTJ
            '9': B-LST
            '10': I-LST
            '11': B-NP
            '12': I-NP
            '13': B-PP
            '14': I-PP
            '15': B-PRT
            '16': I-PRT
            '17': B-SBAR
            '18': I-SBAR
            '19': B-UCP
            '20': I-UCP
            '21': B-VP
            '22': I-VP
    - name: ner_tags
      sequence:
        class_label:
          names:
            '0': O
            '1': B-PER
            '2': I-PER
            '3': B-ORG
            '4': I-ORG
            '5': B-LOC
            '6': I-LOC
            '7': B-MISC
            '8': I-MISC
    - name: ner_labels
      sequence: string
    - name: sentence
      dtype: string
    - name: entities
      struct:
        - name: LOC
          sequence: string
        - name: MISC
          sequence: string
        - name: ORG
          sequence: string
        - name: PER
          sequence: string
  splits:
    - name: train
      num_bytes: 9823344
      num_examples: 14041
    - name: validation
      num_bytes: 2461842
      num_examples: 3250
    - name: test
      num_bytes: 2248983
      num_examples: 3453
  download_size: 3369931
  dataset_size: 14534169
task_categories:
  - text-generation
  - token-classification
language:
  - en
size_categories:
  - 10K<n<100K

Dataset Card for CoNLL-2003 with NER Workflow Enhancements

This dataset is a modified version of the CoNLL-2003 dataset, enhanced to support an LLM-based Named Entity Recognition (NER) workflow. Two new columns, sentence and entities, have been added.

Named Entities

As in the original CoNLL-2003 task, this dataset focuses on four types of named entities:

Persons (PER)
Locations (LOC)
Organizations (ORG)
Miscellaneous entities (MISC) that do not belong to the previous three groups.

Workflow

The LLM is provided with the sentence and a prompt containing NER task instructions. It is then asked to output a dictionary with the identified Named Entities.

Example

For the sentence:

EU rejects German call to boycott British lamb.

The expected output is:

{
  "entities": {
    "LOC": [],
    "MISC": ["German", "British"],
    "ORG": ["EU"],
    "PER": []
  }
}

Original Dataset

You can find the original dataset and its associated documentation at the CoNLL-2003 dataset on Hugging Face.