# MultiMWE: Building a Multi-lingual Multi-Word Expression (MWE) Parallel Corpora

arXiv: https://arxiv.org/abs/2005.10583 · HTML: https://mlsanity.com/paper/2005.10583/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 May 2020.

## Built on by (most cited first, 6 of 6)

- [Translation Quality Assessment: A Brief Survey on Manual and Automatic Methods](https://mlsanity.com/paper/2105.03311/) (2021)
- [HOPE: A Task-Oriented and Human-Centric Evaluation Framework Using Professional Post-Editing Towards More Effective MT Evaluation](https://mlsanity.com/paper/2112.13833/) (2021)
- [Measuring Uncertainty in Translation Quality Evaluation (TQE)](https://mlsanity.com/paper/2111.07699/) (2021)
- [Chinese Character Decomposition for Neural MT with Multi-Word Expressions](https://mlsanity.com/paper/2104.04497/) (2021)
- [Overview of MWE history, challenges, and horizons: standing at the 20th anniversary of the MWE workshop series via MWE-UD2024](https://mlsanity.com/paper/2412.18868/) (2024)
- [An Empirical Study on Chinese Character Decomposition in Multiword Expression-Aware Neural Machine Translation](https://mlsanity.com/paper/2512.15556/) (2025)

## Abstract (arXiv)

Multi-word expressions (MWEs) are a hot topic in research in natural language processing (NLP), including topics such as MWE detection, MWE decomposition, and research investigating the exploitation of MWEs in other NLP fields such as Machine Translation. However, the availability of bilingual or multi-lingual MWE corpora is very limited. The only bilingual MWE corpora that we are aware of is from the PARSEME (PARSing and Multi-word Expressions) EU Project. This is a small collection of only 871 pairs of English-German MWEs. In this paper, we present multi-lingual and bilingual MWE corpora that we have extracted from root parallel corpora. Our collections are 3,159,226 and 143,042 bilingual MWE pairs for German-English and Chinese-English respectively after filtering. We examine the quality of these extracted bilingual MWEs in MT experiments. Our initial experiments applying MWEs in MT show improved translation performances on MWE terms in qualitative analysis and better general evaluation scores in quantitative analysis, on both German-English and Chinese-English language pairs. We follow a standard experimental pipeline to create our MultiMWE corpora which are available online. Researchers can use this free corpus for their own models or use them in a knowledge base as model features.