The goal of IberLEF 2019 is to encourage the research community to organize competitive text processing and understanding tasks with the aim of de ning new research challenges and setting new state-of-the-art results for the Natural Language Processing community, involving at least one of the following Iberian languages: Spanish, Portuguese, Catalan, Basque and Galician. IberLEF 2019 is held together with the XXXV Congreso Internacional de la Sociedad Espan~ola para el Procesamiento del Lenguaje Natural (SEPLN 2019) in Bilbao, Spain, on the 24th of Sep, 2019. It includes the following nine tracks: eHealth Knowledge Discovery (eHealth-KD). The objective of this track is to encourage the development of software technologies to automatically extract a large variety of knowledge from eHealth documents written in the Spanish Language. Factuality Analysis and Classi cation Task (FACT). Its aim is the classication of events in Spanish according to their factuality status.
Named Entity Recognition and Relation Extraction for Portuguese. It proposes several challenges related to Named Entity Recognition and Relation Extraction in texts written in Portuguese.
Authorship and Aggressiveness Analysis in Twitter: case study in Mexican Spanish (MEX-A3T). The track is focused on author pro ling and aggressive speech detection on texts written in Mexican Spanish. Sentiment Analysis Task at SEPLN (TASS). The aim of this task is to promote research into speci c Natural Language Processing techniques for solving problems related to the sentiment analysis of texts written in Spanish.
Medical Document Anonymization task (MEDDOCAN). The aim of this track is the anonymization of medical documents in Spanish, and it is structured into two sub-tasks: NER o set and entity type classi cation and sensitive token detection.
The IberLEF 2019 has had a high participation, in total 179 participants shared out the di erent tracks, submitting 78 papers. The editors