Abstract
Named-entities in free text represent a challenge to text analysis in Machine Translation and Cross Language Information Retrieval. These phrases are often transliterated into another language with a different sound inventory and writing system. Named-entities found in free text are often not listed in bilingual dictionaries. Although it is possible to identify and translate named-entities on the fly without a list of proper names and transliterations, an extensive list of existing transliterations certainly will ensure high precision rate. We use a seed list of proper names and transliterations to train a Machine Transliteration Model. With the model it is possible to extract proper names and their transliterations in monolingual or parallel corpora with high precision and recall rates.
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© 2004 Springer-Verlag Berlin Heidelberg
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Lin, T., Wu, JC., Chang, J.S. (2004). Extraction of Name and Transliteration in Monolingual and Parallel Corpora. In: Frederking, R.E., Taylor, K.B. (eds) Machine Translation: From Real Users to Research. AMTA 2004. Lecture Notes in Computer Science(), vol 3265. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30194-3_20
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DOI: https://doi.org/10.1007/978-3-540-30194-3_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23300-8
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