Knowledge Representation and the Semantics of Natural Language (Cognitive Technologies)
Knowledge Representation and the Semantics of Natural Language (Cognitive Technologies)
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
Automatic Discovery of Part-Whole Relations
Computational Linguistics
Semantic role labeling: an introduction to the special issue
Computational Linguistics
Learning semantic links from a corpus of parallel temporal and causal relations
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Semantic classification of noun phrases using web counts and learning algorithms
ACL '07 Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop
Models for the semantic classification of noun phrases
CLS '04 Proceedings of the HLT-NAACL Workshop on Computational Lexical Semantics
SemEval-2007 task 04: classification of semantic relations between nominals
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Plausible inferencing using extended composition
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Introduction to the CoNLL-2005 shared task: semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Information Processing and Management: an International Journal
SemEval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Unsupervised learning of semantic relation composition
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Semantic role labeling of implicit arguments for nominal predicates
Computational Linguistics
Composition of semantic relations: Theoretical framework and case study
ACM Transactions on Speech and Language Processing (TSLP)
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This paper presents a model to compose semantic relations. The model is independent of any particular set of relations and uses an extended definition for semantic relations. This extended definition includes restrictions on the domain and range of relations and utilizes semantic primitives to characterize them. Primitives capture elementary properties between the arguments of a relation. An algebra for composing semantic primitives is used to automatically identify the resulting relation of composing a pair of compatible relations. Inference axioms are obtained. Axioms take as input a pair of semantic relations and output a new, previously ignored relation. The usefulness of this proposed model is shown using PropBank relations. Eight inference axioms are obtained and their accuracy and productivity are evaluated. The model offers an unsupervised way of accurately extracting additional semantics from text.