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<Paper uid="C04-1156">
  <Title>Knowledge Intensive Word Alignment with KNOWA</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> 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++.</Paragraph>
  </Section>
class="xml-element"></Paper>