This report describes the system developed by the CRIM team for the hypernym discovery
task at SemEval 2018. This system exploits a combination of supervised projection learning …

Curated taxonomies enhance the performance of machine-learning systems via high-quality
structured knowledge. However, manually curating a large and rapidly-evolving taxonomy is …

The hypernymy detection task has been addressed under various frameworks. Previously,
the design of unsupervised hypernymy scores has been extensively studied. In contrast …

Hypernym discovery aims to identify all possible hypernyms of a given term. The most recent
hypernym discovery models exploit multiple mapping functions to project a term to different …

Hypernymy is a semantic relation, expressing the “is-a” relation between a concept and its
instances. Such relations are building blocks for large-scale taxonomies, ontologies and …

摘要上下位关系是自然语言处理领域中的重要概念, 用于描述概念之间的从属关系.
上下位关系的精准预测, 有助于挖掘概念之间的内在层次结构, 是构建大规模语义网络 …

We address hypernymy detection, ie, whether an is-a relationship exists between words (x,
y), with the help of large textual corpora. Most conventional approaches to this task have …

We formulate the problem of hypernym prediction as a sequence generation task, where the
sequences are taxonomy paths in WordNet. Our experiments with encoder-decoder models …

Property inference involves predicting properties for a word from its distributional
representation. We focus on human-generated resources that link words to their properties …

An overview of approaches to automatic extraction of taxonomic relationships (is_a
relationships) from texts, including classical methods based on lexico-semantic patterns and …