IMTKU Textual Entailment System for Recognizing Inference in Text at NTCIR-9 RITE

نویسندگان

  • Min-Yuh Day
  • Re-Yuan Lee
  • Cheng-Tai Liu
  • Chun Tu
  • Chin-Sheng Tseng
  • Loong Tern Yap
  • Allen-Green C. L. Huang
  • Yu-Hsuan Chiu
  • Wei-Ze Hong
چکیده

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 official runs for both BC and MC subtask. In NTCIR-9 RITE task, IMTKU team achieved 0.522 in the CT-MC subtask and 0.556 in the CT-BC subtask.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

IMTKU 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 کامل

IMTKU Textual Entailment System for Recognizing Inference in Text at NTCIR-10 RITE2

In this paper, we describe the IMTKU (Information Management at TamKang University) textual entailment system for recognizing inference in text at NTCIR-10 RITE-2 (Recognizing Inference in Text). We proposed a textual entailment system using a hybrid approach that integrate semantic features and machine learning techniques for recognizing inference in text at NTCIR-10 RITE-2 task. We submitted ...

متن کامل

ZSWSL 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 کامل

BnO at NTCIR-10 RITE: A Strong Shallow Approach and an Inference-based Textual Entailment Recognition System

The BnO team participated in the Recognizing Inference in TExt (RITE) subtask of the NTCIR-10 Workshop [5]. This paper describes our textual entailment recognition system with experimental results for the five Japanes subtasks: BC, MC, EXAMBC, EXAM-SEARCH, and UnitTest. Our appoach includes a shallow method based on word overlap features and named entity recognition; and a novel inferencebased ...

متن کامل

ICL Participation at NTCIR-9 RITE

This paper describes ICL’s participation at NTCIR-9 RITE. We chose BC & MC subtask. Textual entailment is a problem to predict whether an entailment holds for a given test-hypothesis pair. We built an inference model to solve this problem by means of using dependency syntax analysis (by LTP), lexical knowledge base (e.g. CCD), web information (e.g. Baidupedia) and probability method. We used AU...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011