In the medical field, a doctor must have a comprehensive knowledge by reading and writing
narrative documents, and he is responsible for every decision he takes for patients …

Abstract Biomedical Entity Linking (BEL) is the task of mapping of spans of text within
biomedical documents to normalized, unique identifiers within an ontology. This is an …

AMR parsing has experienced an unprecendented increase in performance in the last three
years, due to a mixture of effects including architecture improvements and transfer learning …

The existence of unlinkable (NIL) entities is a major hurdle affecting the performance of
Named Entity Linking approaches, and, consequently, the performance of downstream …

Background Coreference resolution is the task of finding strings in text that have the same
referent as other strings. Failures of coreference resolution are a common cause of false …

This book presents a unique opportunity for constructing a consistent image of collaborative
manual annotation for Natural Language Processing (NLP). NLP has witnessed two major …

This paper introduces MedBERT, a new pre-trained transformer-based model for biomedical
named entity recognition. MedBERT is trained with 57.46 M tokens collected from …

The COVID-19 pandemic has been accompanied by such an explosive increase in media
coverage and scientific publications that researchers find it difficult to keep up. We are …

Information Extraction (IE) from scientific texts can be used to guide readers to the central
information in scientific documents. But narrow IE systems extract only a fraction of the …

Background: Scientific discovery progresses by exploring new and uncharted territory. More
specifically, it advances by a process of transforming unknown unknowns first into known …