Background With the rapid adoption of electronic health records (EHRs), it is desirable to
harvest information and knowledge from EHRs to support automated systems at the point of …

Coreference resolution aims at resolving repeated references to an object in a document
and forms a core component of natural language processing (NLP) research. When used as …

Large pre-trained neural networks such as BERT have had great recent success in NLP,
motivating a growing body of research investigating what aspects of language they are able …

Commonsense reasoning remains a major challenge in AI, and yet, recent progresses on
benchmarks may seem to suggest otherwise. In particular, the recent neural language …

Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

" This book is an absolute necessity for instructors at all levels, as well as an indispensible
reference for researchers. Introducing NLP, computational linguistics, and speech …

This paper develops a novel framework for semantic image retrieval based on the notion of
a scene graph. Our scene graphs represent objects (" man"," boat"), attributes of objects (" …

We present an empirical study of gender bias in coreference resolution systems. We first
introduce a novel, Winograd schema-style set of minimal pair sentences that differ only by …

Relation triples produced by open domain information extraction (open IE) systems are
useful for question answering, inference, and other IE tasks. Traditionally these are extracted …

The CoNLL-2012 shared task involved predicting coreference in English, Chinese, and
Arabic, using the final version, v5. 0, of the OntoNotes corpus. It was a follow-on to the …