Abstract
We maintain that the essential feature that characterizes a Machine Translation approach and sets it apart from other approaches is the kind of knowledge it uses. From this perspective, we argue that Example-Based Machine Translation is sometimes characterized in terms of nonessential features. We show that Example-Based Machine Translation, as long as it is linguistically principled, significantly overlaps with other linguistically principled approaches to Machine Translation. We make a proposal for translation knowledge bases that make such an overlap explicit. We relate our proposal to translation by analogy, which stands out as an inherently example-based technique.
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Turcato, D., Popowich, F. (2003). What is Example-Based Machine Translation?. In: Carl, M., Way, A. (eds) Recent Advances in Example-Based Machine Translation. Text, Speech and Language Technology, vol 21. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0181-6_2
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DOI: https://doi.org/10.1007/978-94-010-0181-6_2
Publisher Name: Springer, Dordrecht
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