The role of domain information in Word Sense Disambiguation
Natural Language Engineering
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Domain kernels for word sense disambiguation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Semantic role labeling via FrameNet, VerbNet and PropBank
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Linking Documents to Encyclopedic Knowledge
IEEE Intelligent Systems
Learning to link with wikipedia
Proceedings of the 17th ACM conference on Information and knowledge management
New features for FrameNet: WordNet mapping
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
Open text semantic parsing using FrameNet and WordNet
HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
SemEval-2007 task 17: English lexical sample, SRL and all words
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
SemEval'07 task 19: frame semantic structure extraction
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Combining word sense and usage for modeling frame semantics
STEP '08 Proceedings of the 2008 Conference on Semantics in Text Processing
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
Probabilistic frame-semantic parsing
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Semi-supervised frame-semantic parsing for unknown predicates
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Wikipedia-based WSD for multilingual frame annotation
Artificial Intelligence
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In this paper, we address the issue of automatic extending lexical resources by exploiting existing knowledge repositories. In particular, we deal with the new task of linking FrameNet and Wikipedia using a word sense disambiguation system that, for a given pair frame -- lexical unit (F, l), finds the Wikipage that best expresses the the meaning of l. The mapping can be exploited to straightforwardly acquire new example sentences and new lexical units, both for English and for all languages available in Wikipedia. In this way, it is possible to easily acquire good-quality data as a starting point for the creation of FrameNet in new languages. The evaluation reported both for the monolingual and the multilingual expansion of FrameNet shows that the approach is promising.