KSU Team's System and Experience at the NTCIR-11 RITE-VAL Task

نویسندگان

  • Tasuku Kimura
  • Hisashi Miyamori
چکیده

This paper describes the systems and results of the team KSU for RITE-VAL task in NTCIR-11. Three different systems were implemented for each of the two subtasks: Fact Validation and System Validation. In Fact Validation subtask, systems were designed respectively based on character overlap, existence of entailment result ’Y’, and voting of entailment results. In System Validation subtask, systems were designed respectively using SVM, Random Forest, and Bagging, with features such as surface features, numerical expressions, location expressions, and named entities. Scores of the formal runs were 52.78% in macro F1 and 66.96% in accuracy with KSU-FV-02 in Fact Validation, and 66.96% in macro F1 and 79.84% in accuracy with KSU-SV01 in System Validation. Also, in System Validation, scores of the unofficial runs were 67.18% in macro F1 and 76.50% in accuracy with KSU-SV-03-C.

برای دانلود 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

NAK Team's System for Recognizing Textual Entailment at the NTCIR-11 RITE-VAL Task

The NAK team participated in the NTCIR-11 RITE-VAL task. This paper describes our textual entailment system and discusses the official results. Our system adopts statistical method: classification of the support vector machine (SVM). For Japanese SV subtask, our best result was 63.19 for macro-F1 score and 74.55 for accuracy. For Japanese FV subtask, our best result was 53.07 for macro-F1 score...

متن کامل

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

WUST at NTCIR-11 RITE-VAL System Validation Task

This paper describes our work in NTCIR-11 on RITE-VAL System Validation task in Simplified Chinese including Binary-class (BC) subtask and Multi-class (MC) subtask. We construct the classification model based on support vector machine to recognize semantic inference in Chinese text pair. In our system, we use multiple features including statistical features, lexical features and syntactic featu...

متن کامل

Experiments for NTCIR-11 RITE-VAL Task at Shibaura Institute of Technology

This paper reports the evaluation results of our textual entailment system at NTCIR-11 RITE-VAL task. We participated in the Japanese System Validation (SV) and Fact Validation (FV) subtasks. In our system, the meaning of a text is represented as a set of dependency triples consisting of two words and their relation. Comparing two sets of dependency triples with respect to conceptual similarity...

متن کامل

Overview of the NTCIR-11 Recognizing Inference in TExt and Validation (RITE-VAL) Task

This paper describes an overview of Recognizing Inference in TExt and Validation (RITE-VAL) task in NTCIR-11. We evaluated systems that automatically recognize semantic relations between sentences such as entailment, contradiction and independence in Japanese (JA), English (EN), Simplified Chinese (CS) and Traditional Chinese (CT). RITE-VAL task has the following two subtasks: Fact Validation s...

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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014