README.md

metadata

dataset_info:
  - config_name: en
    features:
      - name: tokens
        sequence: string
      - name: ner_tags
        sequence:
          class_label:
            names:
              '0': O
              '1': CLINENTITY
              '2': EVENT
              '3': ACTOR
              '4': BODYPART
              '5': TIMEX3
              '6': RML
    splits:
      - name: en
        num_bytes: 507939
        num_examples: 1520
    download_size: 230213492
    dataset_size: 507939
  - config_name: es
    features:
      - name: tokens
        sequence: string
      - name: ner_tags
        sequence:
          class_label:
            names:
              '0': O
              '1': CLINENTITY
              '2': EVENT
              '3': ACTOR
              '4': BODYPART
              '5': TIMEX3
              '6': RML
    splits:
      - name: es
        num_bytes: 501523
        num_examples: 1134
    download_size: 230213492
    dataset_size: 501523
  - config_name: eu
    features:
      - name: tokens
        sequence: string
      - name: ner_tags
        sequence:
          class_label:
            names:
              '0': O
              '1': CLINENTITY
              '2': EVENT
              '3': ACTOR
              '4': BODYPART
              '5': TIMEX3
              '6': RML
    splits:
      - name: eu
        num_bytes: 615175
        num_examples: 3126
    download_size: 230213492
    dataset_size: 615175
  - config_name: fr
    features:
      - name: tokens
        sequence: string
      - name: ner_tags
        sequence:
          class_label:
            names:
              '0': O
              '1': CLINENTITY
              '2': EVENT
              '3': ACTOR
              '4': BODYPART
              '5': TIMEX3
              '6': RML
    splits:
      - name: fr
        num_bytes: 506754
        num_examples: 1109
    download_size: 230213492
    dataset_size: 506754
  - config_name: it
    features:
      - name: tokens
        sequence: string
      - name: ner_tags
        sequence:
          class_label:
            names:
              '0': O
              '1': CLINENTITY
              '2': EVENT
              '3': ACTOR
              '4': BODYPART
              '5': TIMEX3
              '6': RML
    splits:
      - name: it
        num_bytes: 516047
        num_examples: 1146
    download_size: 230213492
    dataset_size: 516047
  - config_name: e3c
    features:
      - name: tokens
        sequence: string
      - name: ner_tags
        sequence:
          class_label:
            names:
              '0': O
              '1': CLINENTITY
              '2': EVENT
              '3': ACTOR
              '4': BODYPART
              '5': TIMEX3
              '6': RML
    splits:
      - name: en.layer1
        num_bytes: 507939
        num_examples: 1520
      - name: en.layer2
        num_bytes: 1017690
        num_examples: 2873
      - name: es.layer1
        num_bytes: 501523
        num_examples: 1134
      - name: es.layer2
        num_bytes: 1002221
        num_examples: 2347
      - name: eu.layer1
        num_bytes: 615175
        num_examples: 3126
      - name: eu.layer2
        num_bytes: 342204
        num_examples: 1594
      - name: fr.layer1
        num_bytes: 506754
        num_examples: 1109
      - name: fr.layer2
        num_bytes: 1027933
        num_examples: 2389
      - name: it.layer1
        num_bytes: 516047
        num_examples: 1146
      - name: it.layer2
        num_bytes: 1071873
        num_examples: 2436
    download_size: 230213492
    dataset_size: 7109359

Dataset Card for E3C

Dataset Description

• Homepage: https://github.com/hltfbk/E3C-Corpus
• Public: True
• Tasks: NER,RE

The European Clinical Case Corpus (E3C) project aims at collecting and
annotating a large corpus of clinical documents in five European languages (Spanish,
Basque, English, French and Italian), which will be freely distributed. Annotations
include temporal information, to allow temporal reasoning on chronologies, and
information about clinical entities based on medical taxonomies, to be used for semantic reasoning.

Citation Information

@report{Magnini2021,
    author = {Bernardo Magnini and Begoña Altuna and Alberto Lavelli and Manuela Speranza
    and Roberto Zanoli and Fondazione Bruno Kessler},
    keywords = {Clinical data,clinical enti-ties,corpus,multilingual,temporal information},
    title = {The E3C Project:
    European Clinical Case Corpus El proyecto E3C: European Clinical Case Corpus},
    url = {https://uts.nlm.nih.gov/uts/umls/home},
    year = {2021},
}