Generalizing case frames using a thesaurus and the MDL principle
Computational Linguistics
Advances in Minimum Description Length: Theory and Applications (Neural Information Processing)
Advances in Minimum Description Length: Theory and Applications (Neural Information Processing)
Japanese case frame construction by coupling the verb and its closest case component
HLT '01 Proceedings of the first international conference on Human language technology research
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
Clustering Syntactic Positions with Similar Semantic Requirements
Computational Linguistics
Question answering based on semantic structures
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
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This article describes an unsupervised strategy to acquire lexico-semantic frames (LSFs) of verbs from sentential parsed corpora (in syntactic level). LSF is a crucial linguistic resource presents a set of semantic elements for exhibiting a meaning of lexeme. The problems of acquiring LSFs consist of verb senses ambiguity, diversity of linguistic usages, and lack of completed elements in a sentence. We propose an specific clustering and combining technique to acquire frame for each verb sense and specify constraints to each frame's slots. Our proposed clustering technique is based on the Minimum Description Length (MDL) principle and using information encoded in features of element instead of its frequency from the corpora.