Dependency syntax analysis using grammar induction and a lexical categories precedence system

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Resumen

The unsupervised approach for syntactic analysis tries to discover the structure of the text using only raw text. In this paper we explore this approach using Grammar Inference Algorithms. Despite of still having room for improvement, our approach tries to minimize the effect of the current limitations of some grammar inductors by adding morphological information before the grammar induction process, and a novel system for converting a shallow parse to dependencies, which reconstructs information about inductor's undiscovered heads by means of a lexical categories precedence system. The performance of our parser, which needs no syntactic tagged resources or rules, trained with a small corpus, is 10% below to that of commercial semi-supervised dependency analyzers for Spanish, and comparable to the state of the art for English.

Idioma originalInglés
Título de la publicación alojadaComputational Linguistics and Intelligent Text Processing - 12th International Conference, CICLing 2011, Proceedings
Páginas109-120
Número de páginas12
EdiciónPART 1
DOI
EstadoPublicada - 2011
Evento12th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2011 - Tokyo, Japón
Duración: 20 feb. 201126 feb. 2011

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NúmeroPART 1
Volumen6608 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia12th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2011
País/TerritorioJapón
CiudadTokyo
Período20/02/1126/02/11

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