---
dataset_info:
  features:
    - name: id
      dtype: string
    - name: document_id
      dtype: int32
    - name: text
      dtype: string
    - name: passages
      list:
        - name: id
          dtype: string
        - name: text
          dtype: string
        - name: offsets
          list: int32
    - name: entities
      list:
        - name: id
          dtype: string
        - name: type
          dtype: string
        - name: text
          dtype: string
        - name: offsets
          list: int32
        - name: semantic_type_id
          dtype: string
        - name: role
          dtype: string
    - name: relations
      list:
        - name: id
          dtype: string
        - name: type
          dtype: string
        - name: contextualAspect
          dtype: string
        - name: contextualModality
          dtype: string
        - name: degree
          dtype: string
        - name: docTimeRel
          dtype: string
        - name: eventType
          dtype: string
        - name: permanence
          dtype: string
        - name: polarity
          dtype: string
        - name: functionInDocument
          dtype: string
        - name: timex3Class
          dtype: string
        - name: value
          dtype: string
        - name: concept_1
          dtype: string
        - name: concept_2
          dtype: string
  config_name: e3c_source
  splits:
    - name: en.layer1
      num_bytes: 1645819
      num_examples: 84
    - name: en.layer2
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      num_examples: 171
    - name: en.layer2.validation
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    - name: en.layer3
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    - name: es.layer1
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    - name: es.layer2.validation
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    - name: es.layer3
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    - name: eu.layer1
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    - name: eu.layer2.validation
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    - name: fr.layer1
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    - name: fr.layer2
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    - name: fr.layer2.validation
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    - name: fr.layer3
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    - name: it.layer1
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    - name: it.layer2
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    - name: it.layer2.validation
      num_bytes: 99549
      num_examples: 18
    - name: it.layer3
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      num_examples: 10213
  download_size: 230213492
  dataset_size: 575318910
---

# Dataset Card for E3C

## Dataset Description

- **Homepage:** https://github.com/hltfbk/E3C-Corpus
- **PubMed** False
- **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

```
@inproceedings{DBLP:conf/clic-it/MagniniALSZ20,
  author       = {Bernardo Magnini and
                  Bego{\~{n}}a Altuna and
                  Alberto Lavelli and
                  Manuela Speranza and
                  Roberto Zanoli},
  editor       = {Johanna Monti and
                  Felice Dell'Orletta and
                  Fabio Tamburini},
  title        = {The {E3C} Project: Collection and Annotation of a Multilingual Corpus
                  of Clinical Cases},
  booktitle    = {Proceedings of the Seventh Italian Conference on Computational Linguistics,
                  CLiC-it 2020, Bologna, Italy, March 1-3, 2021},
  series       = {{CEUR} Workshop Proceedings},
  volume       = {2769},
  publisher    = {CEUR-WS.org},
  year         = {2020},
  url          = {https://ceur-ws.org/Vol-2769/paper\_55.pdf},
  timestamp    = {Fri, 10 Mar 2023 16:22:17 +0100},
  biburl       = {https://dblp.org/rec/conf/clic-it/MagniniALSZ20.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
```

```
@article{Zanoli_Lavelli_Verdi do Amarante_Toti_2024,
title={Assessment of the E3C corpus for the recognition of disorders in clinical texts}, volume={30}, DOI={10.1017/S1351324923000335},
number={4},
journal={Natural Language Engineering},
author={Zanoli, Roberto and Lavelli, Alberto and Verdi do Amarante, Daniel and Toti, Daniele},
year={2024},
pages={851–869}}
```