November 17, 2021
Conference Paper

Improving Synonym Recommendation Using Sentence Context

Abstract

Traditional synonym recommendations often include ill-suited suggestions for writer's specific contexts. We propose a simple approach for contextual synonym recommendation by combining existing human-curated thesauri, e.g. WordNet, with pre-trained language models. We evaluate our technique by curating a set of word-sentence pairs balanced across corpora and parts of speech, then annotating each word-sentence pair with the contextually appropriate set of synonyms. We found that basic language model approaches have higher precision. Approaches leveraging sentence context have higher recall. Overall, the latter contextual approach had the highest F-score.

Published: November 17, 2021

Citation

Glenski M.F., W.I. Sealy, K. Miller, and D.L. Arendt. 2021. Improving Synonym Recommendation Using Sentence Context. In Proceedings of the Second Workshop on Simple and Efficient Natural Language Processing (SustaiNLP 2021), Second Workshop on Simple and Efficient Natural Language Processing, November 10, 2021, Online, 74–78. Stroudsburg, Pennsylvania:Association for Computational Linguistics. PNNL-SA-165392.