Asian and Low-Resource Language Information Processing (TALLIP)


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ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on RITE, Volume 11 Issue 4, December 2012

Introduction to the Special Issue on RITE
Teruko Mitamura, Noriko Kando, Koichi Takeda
Article No.: 12
DOI: 10.1145/2382593.2382594

Evaluating Textual Entailment Recognition for University Entrance Examinations
Yusuke Miyao, Hideki Shima, Hiroshi Kanayama, Teruko Mitamura
Article No.: 13
DOI: 10.1145/2382593.2382595

The present article addresses an attempt to apply questions in university entrance examinations to the evaluation of textual entailment recognition. Questions in several fields, such as history and politics, primarily test the examinee’s...

Learning to Recognize Textual Entailment in Japanese Texts with the Utilization of Machine Translation
Minh Quang Nhat Pham, Minh Le Nguyen, Akira Shimazu
Article No.: 14
DOI: 10.1145/2382593.2382596

Recognizing Textual Entailment (RTE) is a fundamental task in Natural Language Understanding. The task is to decide whether the meaning of a text can be inferred from the meaning of another one. In this article, we conduct an empirical study of...

Recognizing Inference in Texts with Markov Logic Networks
Xipeng Qiu, Ling Cao, Zhao Liu, Xuanjing Huang
Article No.: 15
DOI: 10.1145/2382593.2382597

Recognizing inference in texts (RITE) attracts growing attention of natural language processing (NLP) researchers in recent years. In this article, we propose a novel approach to recognize inference with probabilistic logical reasoning. Our...

Predicate-Argument Structure-Based Textual Entailment Recognition System Exploiting Wide-Coverage Lexical Knowledge
Tomohide Shibata, Sadao Kurohashi
Article No.: 16
DOI: 10.1145/2382593.2382598

This article proposes a predicate-argument structure based Textual Entailment Recognition system exploiting wide-coverage lexical knowledge. Different from conventional machine learning approaches where several features obtained from linguistic...

Validating Contradiction in Texts Using Online Co-Mention Pattern Checking
Chengwei Shih, Chengwei Lee, Richard Tzonghan Tsai, Wenlian Hsu
Article No.: 17
DOI: 10.1145/2382593.2382599

Detecting contradictive statements is a foundational and challenging task for text understanding applications such as textual entailment. In this article, we aim to address the problem of the shortage of specific background knowledge in...

Leveraging Diverse Lexical Resources for Textual Entailment Recognition
Yotaro Watanabe, Junta Mizuno, Eric Nichols, Katsuma Narisawa, Keita Nabeshima, Naoaki Okazaki, Kentaro Inui
Article No.: 18
DOI: 10.1145/2382593.2382600

Since the problem of textual entailment recognition requires capturing semantic relations between diverse expressions of language, linguistic and world knowledge play an important role. In this article, we explore the effectiveness of different...