A maximum entropy approach to natural language processing
Computational Linguistics
Generalized probabilistic LR parsing of natural language (Corpora) with unification-based grammars
Computational Linguistics - Special issue on using large corpora: I
An HPSG parser with CFG filtering
Natural Language Engineering
Japanese dependency structure analysis based on maximum entropy models
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
HPSG-style underspecified Japanese grammar with wide coverage
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Using decision trees to construct a practical parser
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Stochastic lexicalized tree-adjoining grammars
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Japanese dependency analysis using a deterministic finite state transducer
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Japanese dependency analysis using a deterministic finite state transducer
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
ICML '04 Proceedings of the twenty-first international conference on Machine learning
An unsupervised learning method for associative relationships between verb phrases
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
STAR '01 Proceedings of the ACL 2001 Workshop on Sharing Tools and Resources - Volume 15
Efficient deep processing of Japanese
COLING '02 Proceedings of the 3rd workshop on Asian language resources and international standardization - Volume 12
Japanese dependency analysis using cascaded chunking
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Extracting hyponyms of prespecified hypernyms from itemizations and headings in web documents
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Corpus-oriented development of Japanese HPSG parsers
ACLstudent '05 Proceedings of the ACL Student Research Workshop
Unsupervised lexicon induction for clause-level detection of evaluations
Natural Language Engineering
Automatic discovery of attribute words from web documents
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
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This paper describes a hybrid parsing method for Japanese which uses both a hand-crafted grammar and a statistical technique. The key feature of our system is that in order to estimate likelihood for a parse tree, the system uses information taken from alternative partial parse trees generated by the grammar. This utilization of alternative trees enables us to construct a new statistical model called Triplet/Quadruplet Model. We show that this model can capture a certain tendency in Japanese syntactic structures and this point contributes to improvement of parsing accuracy on a shallow level. We report that, with an underspecified HPSG-based grammar and a maximum entropy estimation, our parser achieved high accuracy: 88.6% accuracy in dependency analysis of the EDR annotated corpus, and that it outperformed other purely statistical parsing methods on the same corpus. This result suggests that proper treatment of hand-crafted grammars can contribute to parsing accuracy on a shallow level.