metadata

annotations_creators:
  - expert-generated
languages:
  - es
multilinguality:
  - monolingual
task_categories:
  - text-classification
  - multi-label-text-classification
task_ids:
  - named-entity-recognition

CANTEMIST Corpus

BibTeX citation

If you use these resources in your work, please cite the following paper:

@inproceedings{miranda2020named,
  title={Named entity recognition, concept normalization and clinical coding: Overview of the cantemist track for cancer text mining in spanish, corpus, guidelines, methods and results},
  author={Miranda-Escalada, A and Farr{\'e}, E and Krallinger, M},
  booktitle={Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2020), CEUR Workshop Proceedings},
  year={2020}
}

Digital Object Identifier (DOI) and access to dataset files

TO DO: link to zenodo

Introduction

TO DO: This is a dataset for Named Entity Recognition (NER) from...

Supported Tasks and Leaderboards

Named Entities Recognition, Language Model

Languages

ES - Spanish

Directory structure

cantemist-ner.py
dev.conll
test.conll
train.conll
README.md

Dataset Structure

Data Instances

Three four-column files, one for each split.

Data Fields

Every file has four columns:

1st column: Word form or punctuation symbol
2nd column: Original BRAT file name
3rd column: Spans
4th column: IOB tag

Example:

El                  cc_onco101	662_664	O
informe             cc_onco101	665_672	O
HP                  cc_onco101	673_675	O
es                  cc_onco101	676_678	O
compatible          cc_onco101	679_689	O
con                 cc_onco101	690_693	O
adenocarcinoma      cc_onco101	694_708	B-MORFOLOGIA_NEOPLASIA
moderadamente       cc_onco101	709_722	I-MORFOLOGIA_NEOPLASIA
diferenciado        cc_onco101	723_735	I-MORFOLOGIA_NEOPLASIA
que                 cc_onco101	736_739	O
afecta              cc_onco101	740_746	O
a                   cc_onco101	747_748	O
grasa               cc_onco101	749_754	O
peripancreática     cc_onco101	755_770	O
sobrepasando        cc_onco101	771_783	O
la                  cc_onco101	784_786	O
serosa              cc_onco101	787_793	O
,                   cc_onco101	793_794	O
infiltración        cc_onco101	795_807	O
perineural          cc_onco101	808_818	O
.                   cc_onco101	818_819	O

Data Splits

train: 18,916 tokens
development: 17,656 tokens
test: 10,886 tokens

Dataset Creation

Methodology

TO DO

Curation Rationale

For compatibility with similar datasets in other languages, we followed as close as possible existing curation guidelines.

Source Data

Initial Data Collection and Normalization

TO DO

Who are the source language producers?

TO DO

Annotations

Annotation process

TO DO

Who are the annotators?

TO DO

Dataset Curators

TO DO: Martin?

Personal and Sensitive Information

No personal or sensitive information included.

Contact

TO DO: Casimiro?

License

This work is licensed under a Attribution 4.0 International License.