Local Graph Matching with Active Learning for Recognizing Inference in Text at NTCIR-10
نویسنده
چکیده
This paper describes the textual entailment system developped at Dublin City University for participation in the textual entailment task in NTCIR-10. Our system is a local graph matching-based system with active learning: we explore reducing the unknown words and unknown namedentities, incorporating meaning in parentheses / rhetorical expressions / semantic roles, and employing text understanding technique using simple logic. We deploy an additional feature of language model from deep learning. Our result was 80.49 for macro F1 score, 84.95 for precision for the positive entailment, and 79.95 for recall for negative entailment.
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