The goal of IberLEF 2020 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 2020 is held together with the XXXVI Congreso Internacional SEPLN 2020, Spain, on the 23th of Sep, 2020. It includes the following tracks: Lexicon Analysis Task at SEPLN (ALexS). The goal is to mark those words that can be considered complex, in the sense of di cult comprehension for the reader. CANcer TExt Mining Shared Task ^a tumor named entity recognition (CANTEMIST). CANTEMIST will explore the automatic assignment of eCIE-O-3.1 codes (MorfologA~ a neoplasia) to health-related documents in Spanish language. The CANTEMIST task will be structured into three independent sub-tasks, each taking into account a particular important use case scenario. Corpus del Plan de Impulso a las Tecnolog A~as del Lenguaje (CAPITEL) has three levels of linguistic annotation: morphosyntactic (with lemmas and Universal Dependencies-style POS tags and features), syntactic (following Universal Dependencies v2), and named entities. They propose two IberLEF sub-tasks under the more general where we will use the revised subset of the CAPITEL corpus in two challenges. eHealth Knowledge Discovery (eHealth-KD). This track proposes modeling the human language in a scenario in which Spanish electronic health documents could be machine readable from a semantic point of view. The objective is to encourage the development of software technologies to automatically extract a large variety of knowledge from eHealth documents
written in the Spanish Language. Two tasks are proposed: identi cation and classi cation of key phrases and detection of semantic relations. Factuality Analysis and Classi cation Task (FACT). Its aim is the classication of events in Spanish according to their factuality status. 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.