Publication | Open Access
Learning semantic constraints for the automatic discovery of part-whole relations
236
Citations
8
References
2003
Year
Unknown Venue
Semantic Role LabelingSemantic RelationsEngineeringSemantic WebSemanticsCorpus LinguisticsCausal Relation ExtractionStatistical Relational LearningText MiningNatural Language ProcessingData ScienceComputational LinguisticsLanguage StudiesSemantic ConstraintsMachine TranslationNlp TaskKnowledge DiscoveryComputer ScienceInformation ExtractionSemantic ParsingAutomated ReasoningRelationship ExtractionLinguisticsSemantic Representation
The discovery of semantic relations from text becomes increasingly important for applications such as Question Answering, Information Extraction, Text Summarization, Text Understanding, and others. The semantic relations are detected by checking selectional constraints. This paper presents a method and its results for learning semantic constraints to detect part-whole relations. Twenty constraints were found. Their validity was tested on a 10,000 sentence corpus, and the targeted part-whole relations were detected with an accuracy of 83%.
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