Over the past years, distributed semantic representations have proved to be effective and
flexible keepers of prior knowledge to be integrated into downstream applications. This …

Forming a reliable judgement of a machine learning (ML) model's appropriateness for an
application ecosystem is critical for its responsible use, and requires considering a broad …

The paper describes the results of the first shared task on word sense induction (WSI) for the
Russian language. While similar shared tasks were conducted in the past for some …

Entity set expansion and synonym discovery are two critical NLP tasks. Previous studies
accomplish them separately, without exploring their interdependencies. In this work, we …

In comparative linguistics, colexification refers to the phenomenon of a lexical form
conveying two or more distinct meanings. Existing work on colexification patterns relies on …

Extracting synonyms from dictionaries or corpora is gaining a special attention as synonyms
play an important role in improving NLP application performance. This paper presents a …

Mining entity synonym sets (ie, sets of terms referring to the same entity) is an important task
for many entity-leveraging applications. Previous work either rank terms based on their …

Synonyms refer to different expressions for the same entity in the text and affect entity-centric
text mining research performance. Therefore, synonym recognition has become a promising …

We use dependency triples automatically extracted from a Web-scale corpus to perform
unsupervised semantic frame induction. We cast the frame induction problem as a …

The model's ability to understand synonymous expression is crucial in many kinds of
downstream tasks. It will make the model to better understand the similarity between context …