Computational Linguistics
Automatic extraction of subcategorization from corpora
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
General-to-specific model selection for subcategorization preference
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Automatic acquisition of a large subcategorization dictionary from corpora
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Influence of Conditional Independence Assumption on Verb Subcategorization Detection
TSD '01 Proceedings of the 4th International Conference on Text, Speech and Dialogue
Learning argument/adjunct distinction for Basque
ULA '02 Proceedings of the ACL-02 workshop on Unsupervised lexical acquisition - Volume 9
Learning to predict case markers in Japanese
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Zero-anaphora resolution by learning rich syntactic pattern features
ACM Transactions on Asian Language Information Processing (TALIP)
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Hi-index | 0.00 |
In Japanese, case structure analysis is very important to handle several troublesome characteristics of Japanese such as scrambling, omission of case components, and disappearance of case markers. However, for lack of a wide-coverage case frame dictionary, it has been difficult to perform case structure analysis accurately. Although several methods to construct a case frame dictionary from analyzed corpora have been proposed, they cannot avoid data sparseness problem. This paper proposes an unsupervised method of constructing a case frame dictionary from an enormous raw corpus by using a robust and accurate parser. It also provides a case structure analysis method based on the constructed dictionary.