UTD-SRL: A Pipeline Architecture for Extracting Frame Semantic Structures
نویسندگان
چکیده
This paper describes our system for the task of extracting frame semantic structures in SemEval–2007. The system architecture uses two types of learning models in each part of the task: Support Vector Machines (SVM) and Maximum Entropy (ME). Designed as a pipeline of classifiers, the semantic parsing system obtained competitive precision scores on the test data.
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