Statistical Models for Co-occurrence Data
Statistical Models for Co-occurrence Data
Tagging English text with a probabilistic model
Computational Linguistics
Automatic verb classification based on statistical distributions of argument structure
Computational Linguistics
Probabilistic top-down parsing and language modeling
Computational Linguistics
Assigning function tags to parsed text
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Using semantic preferences to identify verbal participation in role switching alternations
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Three generative, lexicalised models for statistical parsing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Distributional clustering of English words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Clustering verbs semantically according to their alternation behaviour
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Inducing a semantically annotated lexicon via EM-based clustering
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
The Penn Treebank: annotating predicate argument structure
HLT '94 Proceedings of the workshop on Human Language Technology
Statistical parsing with a context-free grammar and word statistics
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Learning verb argument structure from minimally annotated corpora
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Deriving verb-meaning clusters from syntactic structure
HLT-NAACL-TEXTMEANING '03 Proceedings of the HLT-NAACL 2003 workshop on Text meaning - Volume 9
Exploiting a verb lexicon in automatic semantic role labelling
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Zero-anaphora resolution by learning rich syntactic pattern features
ACM Transactions on Asian Language Information Processing (TALIP)
A general feature space for automatic verb classification
Natural Language Engineering
Convolution kernel over packed parse forest
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Grouping alternating schemata in semantic valence dictionary of polish verbs
TSD'11 Proceedings of the 14th international conference on Text, speech and dialogue
Unsupervised learning of verb argument structures
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
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We evaluate probabilistic models of verb argument structure trained on a corpus of verbs and their syntactic arguments. Models designed to represent patterns of verb alternation behavior are compared with generic clustering models in terms of the perplexity assigned to held-out test data. While the specialized models of alternation do not perform as well, closer examination reveals alternation behavior represented implicitly in the generic models.