C4.5: programs for machine learning
C4.5: programs for machine learning
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Automatic verb classification based on statistical distributions of argument structure
Computational Linguistics
Automatic extraction of subcategorization from corpora
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Automatic verb classification using distributions of grammatical features
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Detecting verbal participation in diathesis alternations
ACL '98 Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 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
Automatic extraction of subcategorization frames for Czech
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Clustering verbs semantically according to their alternation behaviour
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Acquiring lexical generalizations from corpora: a case study for diathesis alternations
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Probabilistic models of verb-argument structure
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Statistical filtering and subcategorization frame acquisition
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Semi-supervised verb class discovery using noisy features
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
SEMI-AUTOMATED ANNOTATION AND RETRIEVAL OF DANCE MEDIA OBJECTS
Cybernetics and Systems
A general feature space for automatic verb classification
Natural Language Engineering
Ontology-Based Approach for Semi-automatic Generation of Subcategorization Frames for Spanish Verbs
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
Unsupervised learning of verb argument structures
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
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In this paper we investigate the task of automatically identifying the correct argument structure for a set of verbs. The argument structure of a verb allows us to predict the relationship between the syntactic arguments of a verb and their role in the underlying lexical semantics of the verb. Following the method described in (Merlo and Stevenson, 2001), we exploit the distributions of some selected features from the local context of a verb. These features were extracted from a 23M word WSJ corpus based on part-of-speech tags and phrasal chunks alone. We constructed several decision tree classifiers trained on this data. The best performing classifier achieved an error rate of 33.4%. This work shows that a subcategorization frame (SF) learning algorithm previously applied to Czech (Sarkar and Zeman, 2000) is used to extract SFs in English. The extracted SFs are evaluated by classifying verbs into verb alternation classes.