NAIST at the CLEF 2013 QA4MRE pilot task

Philip Arthur, Graham Neubig, Sakriani Sakti, Tomoki Toda, Satoshi Nakamura

Research output: Contribution to journalConference articleResearchpeer-review

5 Citations (Scopus)

Abstract

This paper describes the Nara Institute of Science and Technology's system for the entrance exam pilot task of CLEF 2013 QA4MRE. The core of the system is a similar to the system for the main task of CLEF 2013 QA4MRE. We use minimum error rate training (MERT) to train the weights of the model and also propose a novel method for MERT with the addition of a threshold that defines the certainty with which we must answer questions. The system received a score of 22% c@1.

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume1179
Publication statusPublished - 1 Jan 2013
Event2013 Cross Language Evaluation Forum Conference, CLEF 2013 - Valencia, Spain
Duration: 23 Sep 201326 Sep 2013

Keywords

  • Discriminative learning
  • Inter-sentence features
  • Linear feature model
  • Machine reading
  • Minimum error rate training
  • Question answering

Cite this

Arthur, P., Neubig, G., Sakti, S., Toda, T., & Nakamura, S. (2013). NAIST at the CLEF 2013 QA4MRE pilot task. CEUR Workshop Proceedings, 1179.
Arthur, Philip ; Neubig, Graham ; Sakti, Sakriani ; Toda, Tomoki ; Nakamura, Satoshi. / NAIST at the CLEF 2013 QA4MRE pilot task. In: CEUR Workshop Proceedings. 2013 ; Vol. 1179.
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Arthur, P, Neubig, G, Sakti, S, Toda, T & Nakamura, S 2013, 'NAIST at the CLEF 2013 QA4MRE pilot task', CEUR Workshop Proceedings, vol. 1179.

NAIST at the CLEF 2013 QA4MRE pilot task. / Arthur, Philip; Neubig, Graham; Sakti, Sakriani; Toda, Tomoki; Nakamura, Satoshi.

In: CEUR Workshop Proceedings, Vol. 1179, 01.01.2013.

Research output: Contribution to journalConference articleResearchpeer-review

TY - JOUR

T1 - NAIST at the CLEF 2013 QA4MRE pilot task

AU - Arthur, Philip

AU - Neubig, Graham

AU - Sakti, Sakriani

AU - Toda, Tomoki

AU - Nakamura, Satoshi

PY - 2013/1/1

Y1 - 2013/1/1

N2 - This paper describes the Nara Institute of Science and Technology's system for the entrance exam pilot task of CLEF 2013 QA4MRE. The core of the system is a similar to the system for the main task of CLEF 2013 QA4MRE. We use minimum error rate training (MERT) to train the weights of the model and also propose a novel method for MERT with the addition of a threshold that defines the certainty with which we must answer questions. The system received a score of 22% c@1.

AB - This paper describes the Nara Institute of Science and Technology's system for the entrance exam pilot task of CLEF 2013 QA4MRE. The core of the system is a similar to the system for the main task of CLEF 2013 QA4MRE. We use minimum error rate training (MERT) to train the weights of the model and also propose a novel method for MERT with the addition of a threshold that defines the certainty with which we must answer questions. The system received a score of 22% c@1.

KW - Discriminative learning

KW - Inter-sentence features

KW - Linear feature model

KW - Machine reading

KW - Minimum error rate training

KW - Question answering

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M3 - Conference article

VL - 1179

JO - CEUR Workshop Proceedings

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Arthur P, Neubig G, Sakti S, Toda T, Nakamura S. NAIST at the CLEF 2013 QA4MRE pilot task. CEUR Workshop Proceedings. 2013 Jan 1;1179.