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A resource-light approach to morpho-syntactic tagging

Autore: Anna Feldman; Jirka Hana
Pubblicazione: Amsterdam ; New York, NY : Rodopi, 2010.
Serie: Language and computers, no. 70.
Edizione/Formato:   eBook : Document : EnglishVedi tutte le edizioni e i formati
Sommario:
While supervised corpus-based methods are highly accurate for different NLP tasks, including morphological tagging, they are difficult to port to other languages because they require resources that are expensive to create. As a result, many languages have no realistic prospect for morpho-syntactic annotation in the foreseeable future. The method presented in this book aims to overcome this problem by significantly  Per saperne di più…
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Dettagli

Genere/formato: Electronic books
Informazioni aggiuntive sul formato: Print version:
Feldman, Anna.
Resource-light approach to morpho-syntactic tagging.
Amsterdam : Rodopi, 2010
(OCoLC)497573700
Tipo materiale: Document, Risorsa internet
Tipo documento Risorsa Internet, Computer file
Tutti gli autori / Collaboratori: Anna Feldman; Jirka Hana
ISBN: 9789042027695 904202769X 9042027681 9789042027688
Numero OCLC: 608352102
Descrizione: 1 online resource (xiv, 185 pages) : illustrations.
Contenuti: Preliminary Material --
Introduction --
Common tagging techniques --
Previous resource-light approaches to NLP --
Languages, corpora and tagsets --
Quantifying language properties --
Resource-light morphological analysis --
Cross-language morphological tagging --
Summary and further work --
Bibliography --
Tagsets we use --
Corpora --
Language properties --
Citation Index.
Titolo della serie: Language and computers, no. 70.
Responsabilità: Anna Feldman and Jirka Hana.

Sinossi:

While supervised corpus-based methods are highly accurate for different NLP tasks, including morphological tagging, they are difficult to port to other languages because they require resources that are expensive to create. As a result, many languages have no realistic prospect for morpho-syntactic annotation in the foreseeable future. The method presented in this book aims to overcome this problem by significantly limiting the necessary data and instead extrapolating the relevant information from another, related language. The approach has been tested on Catalan, Portuguese, and Russian. Although these languages are only relatively resource-poor, the same method can be in principle applied to any inflected language, as long as there is an annotated corpus of a related language available. Time needed for adjusting the system to a new language constitutes a fraction of the time needed for systems with extensive, manually created resources: days instead of years. This book touches upon a number of topics: typology, morphology, corpus linguistics, contrastive linguistics, linguistic annotation, computational linguistics and Natural Language Processing (NLP). Researchers and students who are interested in these scientific areas as well as in cross-lingual studies and applications will greatly benefit from this work. Scholars and practitioners in computer science and linguistics are the prospective readers of this book.

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"F[eldman] & H[ana] have opened a very interesting door, showing us a method with many potential applications to less resourced languages. I suspect there are many other methods behind that door that Per saperne di più…

 
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