Evaluating the Impact of Verbal Multiword Expressions on Machine Translation (2026.acl-long)
Copied to clipboard
| Challenge: | Verbal multiword expressions (VMWEs) are difficult for machine translation because their meanings are often not recoverable from their component words. |
| Approach: | They analyze the impact of verbal idioms, verb-particle constructions, and light verb constructions on machine translation quality from English to multiple languages. |
| Outcome: | The proposed system improves translation quality by focusing on verb idioms, verb-particle constructions and light verb constructions. |
Similar Papers
A Deep Analysis of the Impact of Multiword Expressions and Named Entities on Chinese-English Machine Translations (2024.findings-emnlp)
Copied to clipboard
| Challenge: | a study on the impact of multiword expressions and multiword named entities (NEs) on the performance of Chinese-English machine translation systems is presented. |
| Approach: | They propose to use Chinese multiword expressions and multiword named entities (NEs) to evaluate machine translation performance. |
| Outcome: | The proposed methods show that Chinese-English machine translation systems perform significantly worse on Chinese sentences with most kinds of MWEs and NEs. |
Construction of Large-scale English Verbal Multiword Expression Annotated Corpus (L18-1)
Copied to clipboard
| Challenge: | In this paper, we focus on verbal MWEs, whose accurate recognition is challenging because they could be discontinuous. |
| Approach: | They conduct large-scale annotations of VMWEs on the Wall Street Journal portion of Ontonotes . they first construct a VMwe dictionary based on the english-language Wiktionary . |
| Outcome: | The proposed resource annotates 7,833 VMWE instances belonging to various categories . the authors hope the results will help to develop models for MWE recognition and dependency parsing . |
Verbal Multiword Expression Identification: Do We Need a Sledgehammer to Crack a Nut? (2020.coling-main)
Copied to clipboard
| Challenge: | Multiword expressions (MWEs) are word combinations idiosyncratic with respect to syntax or semantics. |
| Approach: | They propose to use a language-independent system to identify previously seen VMWEs by combining filters to obtain the best averaged F-score over 11 languages and the best score for both seen and unseen VMwes. |
| Outcome: | The proposed system obtains the best averaged F-score over 11 languages and even the best score for both seen and unseen VMWEs due to the high proportion of seen VMwes in texts. |
CoAM: Corpus of All-Type Multiword Expressions (2025.acl-long)
Copied to clipboard
Yusuke Ide, Joshua Tanner, Adam Nohejl, Jacob Hoffman, Justin Vasselli, Hidetaka Kamigaito, Taro Watanabe
| Challenge: | Existing datasets for multiword expressions are inconsistently annotated, limited to a single type of MWE, or limited in size. |
| Approach: | They propose to use a new interface to generate MWE annotations for the first time in a dataset of MWE identification. |
| Outcome: | The proposed model outperforms existing models on the DiMSUM dataset. |
Benchmarking the Performance of Machine Translation Evaluation Metrics with Chinese Multiword Expressions (2024.lrec-main)
Copied to clipboard
| Challenge: | Multiword Expressions (MWEs) are hard nuts for many natural language processing tasks. |
| Approach: | They annotate 28 types of Chinese MWEs and then examine 31 MTE metrics on groups of sentences containing different MWE. |
| Outcome: | The results show that MT systems and MTE metrics still suffer from MWEs . |
If you’ve seen some, you’ve seen them all: Identifying variants of multiword expressions (C18-1)
Copied to clipboard
| Challenge: | Multiword expressions (VMWEs) show idiosyncratic variability, which is challenging for NLP applications. |
| Approach: | They propose to use a model to identify variants of previously seen VMWEs by comparing VMWAs with morpho-syntactic variations. |
| Outcome: | The proposed approach outperforms a baseline by 4 percent points of F-measure on a French corpus. |
Dedicated Language Resources for Interdisciplinary Research on Multiword Expressions: Best Thing since Sliced Bread (2020.lrec-1)
Copied to clipboard
| Challenge: | Multiword expressions are challenging for disciplines like NLP, psycholinguistics and second language acquisition due to their more or less fixed character. |
| Approach: | They propose to develop tools and language resources that are crucial for multifaceted research. |
| Outcome: | The proposed tools and language resources are crucial for this kind of multifaceted research. |
Towards a Variability Measure for Multiword Expressions (N18-2)
Copied to clipboard
| Challenge: | Multiword expressions (MWEs) are groups of words whose meaning does not derive from the meaning of their components and from their syntactic structure in a regular way. |
| Approach: | They propose to use a language-independent measure of variability dedicated to verbal MWEs based on syntactic and discontinuity-related clues to assess its relevance with respect to a linguistic benchmark. |
| Outcome: | The proposed measure is useful for VMWE classification and variant identification on a French corpus. |
Cross-type French Multiword Expression Identification with Pre-trained Masked Language Models (2024.lrec-main)
Copied to clipboard
| Challenge: | Multiword expressions (MWEs) have linguistic features that distinguish them from regular word groupings. |
| Approach: | They propose a combination of two systems that learn verbal multiword expressions and non-verbal MWEs to improve performance on a cross-type dataset . |
| Outcome: | The proposed system improves the F1 score on a french treebank with VMWEs and nVMWES training data. |
A Large Automatically-Acquired All-Words List of Multiword Expressions Scored for Compositionality (L18-1)
Copied to clipboard
| Challenge: | Existing literature on semantically idiosyncratic multiword expressions is limited to English . idiomatic expressions are phraseological units consisting of more than one lexeme and exhibit some kind of idiom. |
| Approach: | They propose to make available a large automatically-acquired all-words list of English multiword expressions scored for compositionality. |
| Outcome: | The proposed list improves the BLEU scores of the English multiword expressions. |