Event extraction (EE) is a crucial information extraction task that aims to extract event
information in texts. Previous methods for EE typically model it as a classification task, which …

Objective There is a lot of information about cancer in Electronic Health Record (EHR) notes
that can be useful for biomedical research provided natural language processing (NLP) …

Event Detection (ED) aims to identify event trigger words from a given text and classify it into
an event type. Most of current methods to ED rely heavily on training instances, and almost …

We present a conditional text generation framework that posits sentential expressions of
possible causes and effects. This framework depends on two novel resources we develop in …

Event extraction aims to identify an event and then extract the arguments participating in the
event. Despite the great success in sentencelevel event extraction, events are more …

The digitalisation of the regulatory compliance process has been an active area of research
for several decades. However, more recently the level of activities in this area has increased …

State-of-the-art vision-language models (VLMs) still have limited performance in structural
knowledge extraction, such as relations between objects. In this work, we present ViStruct, a …

A system which represents knowledge is normally referred to as a knowledge based system
(KBS). This article focuses on surveying publications related to knowledge base modelling …

Museums have a remit to inspire visitors. However, inspiration is a complex, subjective
construct and analyses of inspiration are often laborious. Increased use of social media by …

This paper proposes a representation framework for encoding spatial language in radiology
based on frame semantics. The framework is adopted from the existing SpatialNet …