--- 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 BegoƱa 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}, } ```