Evaluating the LIHLA lexical aligner on Spanish, Brazilian Portuguese and Basque parallel texts

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 sentence-aligned parallel texts. The method has achieved a precision of 92.44% and 85.09% and a recall of 91.13% and 64.66% on Brazilian Portuguese–Spanish and Spanish–Basque parallel texts, respectively.