Machine Learning
Language and Spatial Cognition
Language and Spatial Cognition
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
From grammar to lexicon: unsupervised learning of lexical syntax
Computational Linguistics - Special issue on using large corpora: II
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Role of verbs in document analysis
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Automatic acquisition of a large subcategorization dictionary from corpora
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Role of word sense disambiguation in lexical acquisition: predicting semantics from syntactic cues
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Semantically motivated subcategorization acquisition
ULA '02 Proceedings of the ACL-02 workshop on Unsupervised lexical acquisition - Volume 9
Digraph analysis of dictionary preposition definitions
WSD '02 Proceedings of the ACL-02 workshop on Word sense disambiguation: recent successes and future directions - Volume 8
Preposition semantic classification via Penn Treebank and FrameNet
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
PP-attachment disambiguation using large context
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
SemEval-2007 task 06: word-sense disambiguation of prepositions
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
CLR: integration of FrameNet in a text representation system
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
MELB-YB: preposition sense disambiguation using rich semantic features
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
| Hi-index | 0.00 |
This article studies the issue of argument realization by preposition structures. By examining the preposition structures that are marked as frame elements in FrameNet, the article attempts to give corpus-based attestations to the hypothesized link between deep semantic arguments and their surface syntactic representations. Problems addressed in this article include how argument realization by preposition structures can be predictable from the target lexical unit and the frame it evokes, and why some noncentral prepositions get selected in the argument realization options. The investigation is primarily inspired by Fillmore's work in frame semantics. The source data for this study is derived from a preposition knowledge base that we have recently built by extracting all the semantically annotated preposition structures in FrameNet. The analysis shows that while there are various semantic–syntactic mapping possibilities, for most semantic arguments, the tendency of using central prepositions in their realization expressions is very strong. This is a clear indication that some preposition structures are linked to certain semantic arguments more than they are to others. A similar experiment was conducted using the annotated PropBank corpus to corroborate the supporting evidence found in FrameNet. The results of this study, together with the syntactic–semantic mapping lists of preposition structures can provide raw linguistic data for the study of preposition semantics, lexicography, argument realization, word sense disambiguation, and natural language understanding.