Aligning Multiword Terms Using a Hybrid Approach

  • Arantza Casillas
  • Raquel Martínez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2276)


In the context of parallel corpus alignment research between a pair of languages with various and important distinguishing factors (e.g., structural, lexical, morpho-syntactical), this paper presents an approach that deals with multiword terms alignment. Our system, ALINTEC, implements a hybrid strategy that adds various kinds of linguistic knowledge (an aligned corpus at the sentence level, POS tagging, grammatical patterns, and a bilingual glossary) to quantitative criteria such as frequency and distribution of terms in the corpus. The experiments were undertaken on a parallel corpus consisting on a collection of administrative and legal documents in Spanish and Basque. This pair of languages is representative of the context in which our work is framed. The results show that our approach obtains reasonably good results in aligning terms of a pair of languages of different typology such as Spanish and Basque.


Noun Phrase Natural Language Processing Machine Translation Dynamic Time Warping Distribution Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Arantza Casillas
    • 1
  • Raquel Martínez
    • 2
  1. 1.Facultad de CienciasUniversidad del País VascoSpain
  2. 2.Escuela Superior de CC. Experimentales y TecnologíaUniversidad Rey Juan CarlosSpain

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