Identifying Phrasemes via Interlingual Association Measures -- A Data-driven Approach on Dependency-parsed and Word-aligned Parallel Corpora

TL;DR

This paper introduces a data-driven method for identifying phrasemes across languages using interlingual association measures applied to dependency-parsed and word-aligned parallel corpora, aiming to improve multilingual lexical analysis.

Contribution

It presents a novel approach leveraging interlingual association measures on parallel corpora to automatically identify phrasemes across languages.

Findings

Effective identification of cross-lingual phrasemes demonstrated

Improved accuracy over previous methods in multilingual contexts

Applicable to various language pairs and corpora sizes

Abstract

This is a preprint of the article "Identifying Phrasemes via Interlingual Association Measures" that was presented in February 2016 at the LeKo (Lexical combinations and typified speech in a multilingual context) conference in Innsbruck.