Multiword Expression Processing: A Survey
| Autor: | Gülşen Eryiğit, Lonneke van der Plas, Johanna Monti, Amalia Todirascu, Mathieu Constant, Mike Rosner, Carlos Ramisch |
|---|---|
| Přispěvatelé: | Analyse et Traitement Informatique de la Langue Française (ATILF), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Traitement Automatique du Langage Ecrit et Parlé (TALEP), Laboratoire d'Informatique et Systèmes (LIS), Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Linguistique, Langues et Parole (LILPA), Université de Strasbourg (UNISTRA), ANR-14-CERA-0001,PARSEME-FR,Analyse syntaxique et expressions polylexicales pour le fran?ais(2014), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Analyse et Traitement Informatique de la Langue Française ( ATILF ), Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ), Traitement Automatique du Langage Ecrit et Parlé ( TALEP ), Laboratoire d'Informatique et Systèmes ( LIS ), Aix Marseille Université ( AMU ) -Université de Toulon ( UTLN ) -Centre National de la Recherche Scientifique ( CNRS ) -Aix Marseille Université ( AMU ) -Université de Toulon ( UTLN ) -Centre National de la Recherche Scientifique ( CNRS ), Linguistique, Langues et Parole ( LILPA ), Université de Strasbourg ( UNISTRA ), LILPA, Fonctionnement Discursif et Traduction (LILPA) ( FDT ) |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Linguistics and Language
Machine translation Deep linguistic processing Computer science 02 engineering and technology computer.software_genre Multiword processing natural language processing Language and Linguistics Multiword expression Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Use case Orchestration (computing) natural language processing [SHS.LANGUE]Humanities and Social Sciences/Linguistics 060201 languages & linguistics Parsing business.industry 06 humanities and the arts Computer Science Applications Identification (information) Conceptual framework 0602 languages and literature [ SHS.LANGUE ] Humanities and Social Sciences/Linguistics processing 020201 artificial intelligence & image processing Artificial intelligence business computer Multiword Natural language processing |
| Zdroj: | Computational Linguistics Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2017, 43 (4), pp.837-892. ⟨10.1162/COLI_a_00302⟩ Computational Linguistics, 2017, 43 (4), pp.837-892. ⟨10.1162/COLI_a_00302⟩ Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2017, 43 (4), pp.837-892. 〈http://www.mitpressjournals.org/doi/abs/10.1162/COLI_a_00302〉. 〈10.1162/COLI_a_00302〉 |
| ISSN: | 0891-2017 1530-9312 |
| DOI: | 10.1162/COLI_a_00302⟩ |
| Popis: | International audience; Multiword expressions (MWEs) are a class of linguistic forms spanning conventional word boundaries that are both idiosyncratic and pervasive across different languages. The structure of linguistic processing that depends on the clear distinction between words and phrases has to be re-thought to accommodate MWEs. The issue of MWE handling is crucial for NLP applications, where it raises a number of challenges. The emergence of solutions in the absence of guiding principles motivates this survey, whose aim is not only to provide a focused review of MWE processing, but also to clarify the nature of interactions between MWE processing and downstream applications. We propose a conceptual framework within which challenges and research contributions can be positioned. It offers a shared understanding of what is meant by “MWE processing,” distinguishing the subtasks of MWE discovery and identification. It also elucidates the interactions between MWE processing and two use cases: Parsing and machine translation. Many of the approaches in the literature can be differentiated according to how MWE processing is timed with respect to underlying use cases. We discuss how such orchestration choices affect the scope of MWE-aware systems. For each of the two MWE processing subtasks and for each of the two use cases, we conclude on open issues and research perspectives. |
| Databáze: | OpenAIRE |
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