SemEval-2013 Task 7: The Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge

Abstract

We present the results of the Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge, aiming to bring together researchers in educational NLP technology and textual entailment. The task of giving feedback on student answers requires semantic inference and therefore is related to recognizing textual entailment. Thus, we offered to the community a 5-way student response labeling task, as well as 3-way and 2- way RTE-style tasks on educational data. In addition, a partial entailment task was piloted. We present and compare results from 9 participating teams, and discuss future directions.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2013
Accession Number
ADA587601

Entities

People

  • Chris Brew
  • Claudia Leacock
  • Danilo Giampiccolo
  • Hoa T. Dang
  • Ido Dagan
  • Luisa Bentivogli
  • Myroslava O. Dzikovska
  • Peter E Clark
  • Rodney D. Nielsen

Organizations

  • University of North Texas

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Base Lines
  • Computational Linguistics
  • Computational Science
  • Computer Languages
  • Data Mining
  • Data Sets
  • Dialogue Systems
  • Feedback
  • Language
  • Linguistics
  • Machine Learning
  • Natural Language Processing
  • Supervised Machine Learning
  • Test Sets

Fields of Study

  • Education

Readers

  • Computational Linguistics
  • STEM Education

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Information Retrieval