
Contents
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28.1 Introduction 28.1 Introduction
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28.2 Linguistic Characterization of MWEs 28.2 Linguistic Characterization of MWEs
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28.2.1 Words, Lexemes, and Tokens 28.2.1 Words, Lexemes, and Tokens
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28.2.2 Multiword Expressions 28.2.2 Multiword Expressions
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28.2.3 Compositionality and Conventionality 28.2.3 Compositionality and Conventionality
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28.2.4 Other Characteristics of MWEs 28.2.4 Other Characteristics of MWEs
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Limited variability Limited variability
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No word-for-word translation No word-for-word translation
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Properties that are challenging for MWE processing Properties that are challenging for MWE processing
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Computational processing of MWEs Computational processing of MWEs
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28.3 Type-Based MWE Discovery 28.3 Type-Based MWE Discovery
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28.3.1 Morphosyntactic Patterns 28.3.1 Morphosyntactic Patterns
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28.3.2 Association Scores 28.3.2 Association Scores
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28.3.3 Substitutability 28.3.3 Substitutability
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28.3.4 Semantic Interpretation 28.3.4 Semantic Interpretation
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28.3.5 Multilingual Discovery 28.3.5 Multilingual Discovery
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28.4 Token-Based MWE Identification 28.4 Token-Based MWE Identification
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28.4.1 Lexicon Lookup Methods 28.4.1 Lexicon Lookup Methods
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28.4.2 Tagging-Based Methods 28.4.2 Tagging-Based Methods
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28.4.3 Disambiguation Methods 28.4.3 Disambiguation Methods
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28.4.4 Parsing-Based Methods 28.4.4 Parsing-Based Methods
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28.5 MWE-Aware Applications 28.5 MWE-Aware Applications
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28.5.1 Machine Translation 28.5.1 Machine Translation
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28.5.2 Lexicography and Terminology 28.5.2 Lexicography and Terminology
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28.5.3 Information Extraction and Retrieval 28.5.3 Information Extraction and Retrieval
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Further Reading and Relevant Resources Further Reading and Relevant Resources
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References References
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28 Computational Treatment of Multiword Expressions
Get accessCarlos Ramisch is an Assistant Professor and Researcher in computational linguistics at Aix-Marseille University. He is passionate about languages, in particular about multiword expressions. His research goal is to integrate multiword expressions processing into NLP applications, covering their discovery, identification, representation, and translation. He was co-chair of several editions of the MWE workshop, participates actively in the PARSEME community, co-organizes the PARSEME shared tasks, and developed the MWEtoolkit, a free tool for MWE processing.
Aline Villavicencio is Chair of Natural Language Processing at the University of Sheffield and received her PhD from the University of Cambridge (UK). She was a visiting scholar at the Massachusetts Institute of Technology (USA) and the École Normale Supérieure (France). She has served on the editorial board of journals, including the Journal of Natural Language Engineering and Transactions of the Association for Computational Linguistics; and her research interests on multi-word expressions and on cognitive aspects of computational language acquisition resulted in co-edited special issues and books dedicated to these topics.
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Published:05 April 2018
Cite
Abstract
In natural-language processing, multiword expressions (MWEs) have been the focus of much attention in their many forms, including idioms, nominal compounds, verbal expressions, and collocations. In addition to their relevance for lexicographic and terminographic work, their ubiquity in language affects the performance of tasks like parsing, word sense disambiguation, and natural-language generation. They lend a mark of naturalness and fluency to applications that can deal with them, ranging from machine translation to information retrieval. This chapter presents an overview of their linguistic characteristics and discusses a variety of proposals for incorporating them into language technology, covering type-based discovery, token-based identification, and MWE-aware language technology applications.
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