Objectives Question answering (QA) systems have the potential to improve the quality of
clinical care by providing health professionals with the latest and most relevant evidence …

Background Detecting event triggers in biomedical texts, which contain domain knowledge
and context-dependent terms, is more challenging than in general-domain texts. Most state …

Motivation Biomedical entity linking (BEL) is the task of grounding entity mentions to a given
knowledge base (KB). Recently, neural name-based methods, system identifying the most …

Document-level event argument extraction (DEAE) aims to identify the arguments
corresponding to the roles of a given event type in a document. However, arguments …

Biomedical relation extraction (BioRE) is the task of automatically extracting and classifying
relations between two biomedical entities in biomedical literature. Recent advances in …

The pathway curation task involves analyzing scientific literature to identify and represent
cellular processes as pathways. This process, often time-consuming and labor-intensive …

Biomedical Event Extraction (BEE) is a crucial task in biomedical natural language
processing, aiming to identify molecular events involving genes, proteins, and other …

The advent of pre-trained language models (LMs) has enabled unprecedented advances in
the Natural Language Processing (NLP) field. In this respect, various specialised LMs for the …

In document-level event extraction tasks, multiple event types often coexist within a
document (the multi-event problem), and arguments may play different roles across different …

Biomedical relation extraction (BioRE) is the task of automatically extracting and classifying
relations between two biomedical entities in biomedical literature. Recent advances in …