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---
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},
}
```