MEDDOPROF corpus: sample set
| dc.contributor.author | Salvador Lima López | |
| dc.contributor.author | Eulàlia Farré-Maduell | |
| dc.contributor.author | Vicent Brivá-Iglesias | |
| dc.contributor.author | Antonio Miranda-Escalada | |
| dc.contributor.author | Martin Krallinger | |
| dc.coverage.spatial | Bolivia | |
| dc.date.accessioned | 2026-03-22T20:54:40Z | |
| dc.date.available | 2026-03-22T20:54:40Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | The <strong>MEDDOPROF corpus</strong> is a collection of 2000 clinical cases from over 20 different specialties annotated with professions, employment statuses and other work-related activities. It is used for the MEDDOPROF Shared Task on occupations and employment status detection and normalization in Spanish medical documents, which will be celebrated as part of IberLEF 2021. The sample set is composed of <strong>15 clinical cases</strong> extracted from the training set from four different specialties: radiology, oncology, psychiatry and occupational health. The files are distributed as follows: - For the <strong>subtask 1 (MEDDOPROF-NER)</strong>, annotations are distributed in Brat standoff format with PROFESION/SITUACION_LABORAL tags only. - For the<strong> subtask 2 (MEDDOPROF-CLASS)</strong>, annotations are distributed in Brat standoff format with PACIENTE/FAMILIAR/SANITARIO/OTROS tags only. - For the <strong>subtask 3 (MEDDOPROF-NORM)</strong>, annotations are distributed in a tab-separated file (TSV) with a code column that includes the mapping of entities to ESCO and SNOMED-CT. For further information, please visit https://temu.bsc.es/meddoprof/ or email us at encargo-pln-life@bsc.es | |
| dc.identifier.doi | 10.5281/zenodo.4518733 | |
| dc.identifier.uri | https://doi.org/10.5281/zenodo.4518733 | |
| dc.identifier.uri | https://andeanlibrary.org/handle/123456789/84800 | |
| dc.language.iso | en | |
| dc.publisher | European Organization for Nuclear Research | |
| dc.relation.ispartof | Zenodo (CERN European Organization for Nuclear Research) | |
| dc.source | Barcelona Supercomputing Center | |
| dc.subject | Sample (material) | |
| dc.subject | Set (abstract data type) | |
| dc.subject | Natural language processing | |
| dc.subject | Computer science | |
| dc.subject | Artificial intelligence | |
| dc.title | MEDDOPROF corpus: sample set | |
| dc.type | dataset |