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Learning Machine Translation$
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Cyril Goutte, Nicola Cancedda, Marc Dymetman, and George Foster

Print publication date: 2008

Print ISBN-13: 9780262072977

Published to MIT Press Scholarship Online: August 2013

DOI: 10.7551/mitpress/9780262072977.001.0001

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Automatic Construction of Multilingual Name Dictionaries

Automatic Construction of Multilingual Name Dictionaries

(p.59) 3 Automatic Construction of Multilingual Name Dictionaries
Learning Machine Translation

Bruno Pouliquen

Ralf Steinberger

The MIT Press

Machine translation and other natural language processing systems often experience performance loss when processing texts with unknown words, such as proper names. Proper name dictionaries are rare and can never be complete because new names are being made up all the time. A solution to overcome this problem would be to recognize and mark a named entity in text before translating it and to carry over the named entity untranslated. This chapter presents a method and a system that recognizes named entities of the types “person” and—to some extent—“organization” in multilingual text collections, and automatically identifies which of the newly identified names are variants of a known name. By doing this for nineteen languages and in the course of years, a multilingual name dictionary has been developed containing over 630,000 names and over 135,000 known variants, with up to 170 multilingual variants for a single name. The automatically generated name dictionary is used daily in the publicly accessible multilingual news aggregation and analysis system NewsExplorer.

Keywords:   machine translation, name recognition, multilingual recognition, proper names, language processing systems NewsExplorer

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