IKOMA at TAC2011: A Method for Recognizing Textual Entailment using Lexical-level and Sentence Structure-level features
Masaaki Tsuchida, Kai Ishikawa · Theory and applications of categories · 2011
This paper describes the Recognizing Textual Entailment (RTE) system that our teams developed for TAC 2011. Our system combines the entailment score calculated by lexicallevel matching with the machine-learningbased filtering mechanism using various features obtained from lexical-level, chunk-level and predicate argument structure-level information. In the filtering mechanism, we try to discard the T-H pairs that have high entailment score and are actually not entailment. That is, for filtering false positive T-H pairs caused by our lexical-level manner, we use additional information like features from word chunks and predicate-argument structures.