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Syntactic-Semantic Classes of Context-Sensitive Synonyms Based on a Bilingual Corpus

Publication at Faculty of Mathematics and Physics |
2020

Abstract

This paper summarizes findings of a three-year study on verb synonymy in translation based on both syntactic and semantic criteria and reports on recent results extending this work. Primary language resources used are existing Czech and English lexical and corpus resources, namely the Prague Dependency Treebank-style valency lexicons, FrameNet, VerbNet, PropBank, WordNet and the parallel Prague Czech-English Dependency Treebank, which contains deep syntactic and partially semantic annotation of running texts.

The resulting lexicon (called formerly CzEngClass, now SynSemClass) and all associated resources linked to the existing lexicons and corpora following from this project are publicly and freely available. While the project proper assumes manual annotation work, we expect to use the resulting resource (together with the existing ones) as a necessary resource for developing automatic methods for extending such a lexicon, or creating similar lexicons for other languages.