Automatic labeling of semantic roles
Computational Linguistics
Class-Based Construction of a Verb Lexicon
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Mapping lexical entries in a verbs database to WordNet senses
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Using predicate-argument structures for information extraction
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Maximum entropy models for FrameNet classification
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Inducing frame semantic verb classes from WordNet and LDOCE
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
An algorithm for open text semantic parsing
ROMAND '04 Proceedings of the 3rd Workshop on RObust Methods in Analysis of Natural Language Data
Putting pieces together: combining FrameNet, VerbNet and WordNet for robust semantic parsing
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Increasing the coverage of a domain independent dialogue lexicon with VerbNet
ScaNaLU '06 Proceedings of the Third Workshop on Scalable Natural Language Understanding
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Semantic resources of predicate-argument structure have high potential to enable increased quality in language understanding. Several alternative frame collections exist, but they cover different sets of predicates and use different role sets. We integrate semantic frame information given a predicate verb using three available collections: FrameNet, PropBank, and the LCS database. For each word sense in WordNet, we automatically assign the corresponding FrameNet frame and align frame roles between FrameNet and PropBank frames and between FrameNet and LCS frames, and verify the results manually. The results are avilable as part of ISI’s Omega ontology.