The task of resolving repeated objects in natural languages is known as coreference
resolution, and it is an important part of modern natural language processing. It is classified …

In this paper we introduce a new publicly available dataset for verification against textual
sources, FEVER: Fact Extraction and VERification. It consists of 185,445 claims generated …

Organized relational knowledge in the form of “knowledge graphs” is important for many
applications. However, the ability to populate knowledge bases with facts automatically …

In this paper, we study the problem of learning probabilistic logical rules for inductive and
interpretable link prediction. Despite the importance of inductive link prediction, most …

Event detection (ED), which means identifying event trigger words and classifying event
types, is the first and most fundamental step for extracting event knowledge from plain text …

This survey presents a comprehensive description of recent neural entity linking (EL)
systems developed since 2015 as a result of the “deep learning revolution” in natural …

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

Event extraction (EE) has considerably benefited from pre-trained language models (PLMs)
by fine-tuning. However, existing pre-training methods have not involved modeling event …

Existing event extraction methods classify each argument role independently, ignoring the
conceptual correlations between different argument roles. In this paper, we propose a …

Motivation: The scientific literature embeds an enormous amount of relational knowledge,
encompassing interactions between biomedical entities, like proteins, drugs, and symptoms …