Background Temporal relations between clinical events play an important role in clinical
assessment and decision making. Extracting such relations from free text data is a …

Objectives: We present a review of recent advances in clinical Natural Language Processing
(NLP), with a focus on semantic analysis and key subtasks that support such analysis …

Emotion, a pervasive aspect of human experience, has long been of interest to social and
behavioural sciences. It is now the subject of multi-disciplinary research also in …

The diverse relationships among real-world events, including coreference, temporal, causal,
and subevent relations, are fundamental to understanding natural languages. However, two …

This article discusses the requirements of a formal specification for the annotation of
temporal information in clinical narratives. We discuss the implementation and extension of …

In this article, we describe a system that reads news articles in four different languages and
detects what happened, who is involved, where and when. This event-centric information is …

In this work we present an annotation framework to capture causality between events,
inspired by TimeML, and a language resource covering both temporal and causal relations …

The EU-funded project Lynx focuses on the creation of a knowledge graph for the legal
domain (Legal Knowledge Graph, LKG) and its use for the semantic processing, analysis …

For humans, understanding a natural language sentence or discourse is so effortless that
we hardly ever think about it. For machines, however, the task of interpreting natural …

This paper presents Gesture AMR, an extension to Abstract Meaning Representation (AMR),
that captures the meaning of gesture. In developing Gesture AMR, we consider how gesture …