Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

Semantic representation is receiving growing attention in NLP in the past few years, and
many proposals for semantic schemes (eg, AMR, UCCA, GMB, UDS) have been put forth …

Pretrained Masked Language Models (MLMs) have revolutionised NLP in recent years.
However, previous work has indicated that off-the-shelf MLMs are not effective as universal …

The lemon model has become the primary mechanism for the representation of lexical data
on the Semantic Web. The lemon model has been further developed in the context of the …

Abstract We present Attract-Repel, an algorithm for improving the semantic quality of word
vectors by injecting constraints extracted from lexical resources. Attract-Repel facilitates the …

Transformer-based language models (LMs) pretrained on large text collections implicitly
store a wealth of lexical semantic knowledge, but it is non-trivial to extract that knowledge …

Multilinguality is an important topic for knowledge bases, especially Wikidata, that was build
to serve the multilingual requirements of an international community. Its labels are the way …

In this paper we present a Web interface and a RESTful API for our state-of-the-art
multilingual word sense disambiguation and entity linking system. The Web interface has …

Ontology matching is an integral part for establishing semantic interoperability. One of the
main challenges within the ontology matching operation is semantic heterogeneity, ie …

A large number of machine translation approaches have recently been developed to
facilitate the fluid migration of content across languages. However, the literature suggests …