Semantic annotation is a crucial part of achieving the vision of the Semantic Web and has
long been a research topic among various communities. The most challenging problem in …

Motivation The biomedical community's collective understanding of how chemicals, genes
and phenotypes interact is distributed across the text of over 24 million research articles …

We explore unsupervised approaches to relation extraction between two named entities; for
instance, the semantic bornIn relation between a person and location entity. Concretely, we …

Recent advances in relation extraction with deep neural architectures have achieved
excellent performance. However, current models still suffer from two main drawbacks: 1) …

Abstract Current techniques for Open Information Extraction (OIE) focus on the extraction of
binary facts and suffer significant quality loss for the task of extracting higher order N-ary …

The wealth of interaction information provided in biomedical articles motivated the
implementation of text mining approaches to automatically extract biomedical relations. This …

Texts have become an important spatial data resource. Interpretation of unstructured
geoscience texts using natural language processing methods can effectively facilitate the …

We describe the use of a hierarchical topic model for automatically identifying syntactic and
lexical patterns that explicitly state ontological relations. We leverage distant supervision …

In this paper, we study the problem of mining temporal semantic relations between entities.
The goal of the studied problem is to mine and annotate a semantic relation with temporal …

Named entity relation extraction is an important subject in the field of information extraction.
Although many English extractors have achieved reasonable performance, an effective …