A resource-light approach to morpho-syntactic tagging

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書誌事項

A resource-light approach to morpho-syntactic tagging

Anna Feldman and Jirka Hana

（Language and computers : studies in practical linguistics, no. 70）

Rodopi, 2010

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

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.

目次

  • List of tables List of figures Preface 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 Appendices: Tagsets we use
  • Corpora
  • Language properties Citation Index

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