Morphological analysis and disambiguation for Breton.

In this paper we present an extended description of two resources for natural language processing of Breton, a morphological analyser and constraint grammar-based disambiguator. The constraint grammar was developed using a novel methodology by a linguist and a language consultant creating rules to s...

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Publicado en:Language Resources & Evaluation Vol. 55; no. 2; pp. 431 - 474
Autores principales: Tyers, Francis M., Howell, Nick
Formato: Artículo
Publicado: Springer Nature Jun2021
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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          Tyers, Francis M.
          Howell, Nick
        affil:
          Department of Linguistics, Indiana University, Bloomington, United States
          School of Linguistics, Higher School of Economics, Moscow, Russia
      su:
        Natural language processing
        Machine translating
        Natural resources
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          Natural language processing
          Machine translating
          Natural resources
      keyword:
        Breton
        NLP
        Pipeline
      ab: In this paper we present an extended description of two resources for natural language processing of Breton, a morphological analyser and constraint grammar-based disambiguator. The constraint grammar was developed using a novel methodology by a linguist and a language consultant creating rules to solve specific errors in disambiguation in a machine translation system. In addition we introduce a new morphologically-disambiguated corpus of Breton and evaluate both the morphological analyser and constraint grammar for coverage and accuracy. For comparison we use the same corpus to train several reference systems for part-of-speech tagging and lemmatisation and compare the performance. The experiments show that our system outperforms the reference systems by a wide margin when the reference systems are trained without an external full-form list, and performs comparably when they are trained with a full-form list generated from our morphological analyser.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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      custom: Language Resources & Evaluation is a copyright of Springer, 2021. All Rights Reserved.
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          year: 2021
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