LIHLA: A lexical aligner based on language-independent heuristics

نویسندگان

  • Helena de Medeiros Caseli
  • Mikel L. Forcada
چکیده

Alignment of words and multiword units plays an important role in many natural language processing applications, such as example-based machine translation, transfer rule learning for machine translation, bilingual lexicography, word sense disambiguation, etc. In this paper we describe LIHLA, a lexical aligner which uses bilingual probabilistic lexicons generated by a freely available set of tools (NATools) and language-independent heuristics to find links between single words and multiword units in Brazilian Portuguese, Spanish and English parallel texts. The method has achieved a precision of 92.48% and 84.35% and a recall of 88.32% and 76.39% on Brazilian Portuguese–Spanish and Brazilian Portuguese–English parallel texts, respectively.

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تاریخ انتشار 2005