UTD: Classifying Semantic Relations by Combining Lexical and Semantic Resources 论文

2010引用 219
Natural Language Processing TechniquesTopic ModelingBiomedical Text Mining and Ontologies

摘要

This paper describes our system for SemEval-2010 Task 8 on multi-way classification of semantic relations between nominals. First, the type of semantic relation is classified. Then a relation typespecific classifier determines the relation direction. Classification is performed using SVM classifiers and a number of features that capture the context, semantic role affiliation, and possible pre-existing relations of the nominals. This approach achieved an F1 score of 82.19 % and an accuracy of 77.92%. 1