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Pattern-based unsupervised parsing method

Published online by Cambridge University Press:  04 June 2014

JESÚS SANTAMARÍA  and
LOURDES ARAUJO
JESÚS SANTAMARÍA
Affiliation:
Lenguajes y Sistemas Informáticos, Universidad Nacional de Educación a Distancia (UNED), Madrid 28040, Spain email: jsant@lsi.uned.es, lurdes@lsi.uned.es
LOURDES ARAUJO
Affiliation:
Lenguajes y Sistemas Informáticos, Universidad Nacional de Educación a Distancia (UNED), Madrid 28040, Spain email: jsant@lsi.uned.es, lurdes@lsi.uned.es
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Abstract

We have developed a heuristic method for unsupervised parsing of unrestricted text. Our method relies on detecting certain patterns of part-of-speech tag sequences of words in sentences. This detection is based on statistical data obtained from the corpus and allows us to classify part-of-speech tags into classes that play specific roles in the parse trees. These classes are then used to construct the parse tree of new sentences via a set of deterministic rules. Aiming to asses the viability of the method on different languages, we have tested it on English, Spanish, Italian, Hebrew, German, and Chinese. We have obtained a significant improvement over other unsupervised approaches for some languages, including English, and provided, as far as we know, the first results of this kind for others.

Type
Articles
Information
Natural Language Engineering , Volume 22 , Issue 3 , May 2016 , pp. 397 - 422
Copyright
Copyright © Cambridge University Press 2014 

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