Methods for unsupervised hypernym detection may broadly be categorized according to two
paradigms: pattern-based and distributional methods. In this paper, we study the …

Recent work on word embeddings has shown that simple vector subtraction over pre-trained
embeddings is surprisingly effective at capturing different lexical relations, despite lacking …

This paper describes the SemEval 2018 Shared Task on Hypernym Discovery. We put
forward this task as a complementary benchmark for modeling hypernymy, a problem which …

The fundamental role of hypernymy in NLP has motivated the development of many
methods for the automatic identification of this relation, most of which rely on word …

We introduce HyperLex—a data set and evaluation resource that quantifies the extent of the
semantic category membership, that is, type-of relation, also known as hyponymy …

The number of databases that provide various measurements of lexical properties for
psycholinguistic research has increased rapidly in recent years. The proliferation of lexical …

We consider the task of inferring is-a relationships from large text corpora. For this purpose,
we propose a new method combining hyperbolic embeddings and Hearst patterns. This …

Cross-lingual word embeddings are becoming increasingly important in multilingual NLP.
Recently, it has been shown that these embeddings can be effectively learned by aligning …

Pre-trained language models have been found to capture a surprisingly rich amount of
lexical knowledge, ranging from commonsense properties of everyday concepts to detailed …

Modeling hypernymy, such as poodle is-a dog, is an important generalization aid to many
NLP tasks, such as entailment, coreference, relation extraction, and question answering …