Open AccessPredicting and Using a Pragmatic Component of Lexical Aspect
Author(s) -
Sharid Loáiciga,
Cristina Grisot
Publication year - 2016
Publication title -
linguistic issues in language technology
Language(s) - English
Resource type - Journals
eISSN - 1945-3590
pISSN - 1945-3604
DOI - 10.33011/lilt.v13i.1389
Subject(s) - computer science , component (thermodynamics) , natural language processing , machine translation , artificial intelligence , phrase , annotation , translation (biology) , rule based machine translation , example based machine translation , lexical choice , lexical item , biochemistry , chemistry , physics , messenger rna , gene , thermodynamics
This paper proposes a method for improving the results of a statistical Machine Translation system using boundedness, a pragmatic component of the verbal phrase’s lexical aspect. First, the paper presents manual and automatic annotation experiments for lexical aspect in English-French parallel corpora. It will be shown that this aspectual property is identified and classified with ease both by humans and by automatic systems. Second, Statistical Machine Translation experiments using the boundedness annotations are presented. These experiments show that the information regarding lexical aspect is useful to improve the output of a Machine Translation system in terms of better choices of verbal tenses in the target language, as well as better lexical choices. Ultimately, this work aims at providing a method for the automatic annotation of data with boundedness information and at contributing to Machine Translation by taking into account linguistic data.