Knowledge intensive word alignment with KNOWA
Emanuele Pianta, Luisa Bentivogli · 2004
In this paper we present KNOWA, an English/Italian word aligner, developed at ITC-irst, which relies mostly on information contained in bilingual dictionaries.The performances of KNOWA are compared with those of GIZA++, a state of the art statistics-based alignment algorithm.The two algorithms are evaluated on the EuroCor and MultiSemCor tasks, that is on two English/Italian publicly available parallel corpora.The results of the evaluation show that, given the nature and the size of the available English-Italian parallel corpora, a language-resource-based word aligner such as KNOWA can outperform a fully statistics-based algorithm such as GIZA++.