The WHUTE System in NTCIR-10 RITE Task
نویسندگان
چکیده
This paper describes our system of recognizing textual entailment for RITE Traditional and Simplified Chinese subtasks at NTCIR10. We build a textual entailment recognition framework and implement a system that employs features of three categories, including string, structure and linguistic features, for the recognition. In addition, an entailment transformation approach is leveraged to align text fragments in each pair. We also utilize a cascaded recognition strategy, which first judge entailment or no entailment, and then forward, bidirectional, contradiction or independence relation of each text pair in turn. Official results show that our system achieves a 65.55% MacroF1 performance in Traditional BC subtask, a 45.50% in Traditional MC subtask, a 61.65% in Simplified BC subtask and a 46.79% in Simplified MC subtask. In IR4QA subtasks, our system achieves a 27.33% WorseRanking Top1 accuracy in Traditional subtask and a 18.67% in Simplified subtask.
منابع مشابه
The WHUTE System in NTCIR-9 RITE Task
This paper describes our system of recognizing textual entailment for RITE Chinese subtask at NTCIR-9. We build a textual entailment recognition framework and implement a system that employs string, syntactic, semantic and some specific features for the recognition. To improve the system’s performance, a twostage recognition strategy is utilized, which first judge entailment or no entailment, a...
متن کاملThe WHUTE System in NTCIR-11 RITE-VAL Task
This paper describes our system of recognizing textual entailment for RITEVAL System Validation and Fact Validation subtasks at NTCIR-11. For System Validation subtask, we employ a transformation model and acquire entailment rules by extracting synonyms and inferable expressions from resources such as lexicons and knowledge bases. Also, a cascaded entailment recognition model is employed to rec...
متن کاملZSWSL Text Entailment Recognizing System at NTCIR-9 RITE Task
This paper describes our system on simplified Chinese textual entailment recognizing RITE task at NTCIR-9. Both lexical and semantic features are extracted using NLP methods. Three classification models are used and compared for the classification task, Rule-based algorithms, SVM and C4.5. C4.5 gives the best result on testing data set. Evaluation at NTCIR-9 RITE shows 72% accuracy on BC subtas...
متن کاملIMTKU Textual Entailment System for Recognizing Inference in Text at NTCIR-11 RITE-VAL
In this paper, we describe the IMTKU (Information Management at TamKang University) textual entailment system for recognizing inference in text at NTCIR-11 RITE-VAL (Recognizing Inference in Text). We proposed a textual entailment system using statistics approach that integrate semantic features and machine learning techniques for recognizing inference in text at NTCIR-11 RITEVAL task. We submi...
متن کاملIMTKU Textual Entailment System for Recognizing Inference in Text at NTCIR-9 RITE
In this paper, we describe the IMTKU (Information Management at TamKang University) textual entailment system for recognizing inference in text at NTCIR-9 RITE (Recognizing Inference in Text). We proposed a textual entailment system using a hybrid approach that integrate knowledge based and machine learning techniques for recognizing inference in text at NTCIR-9 RITE task. We submitted 3 offici...
متن کامل