Multiple Choice Question Corpus Analysis for Distractor Characterization

Van-Minh Pho, Thibault André, Anne-Laure Ligozat, Brigitte Grau, Gabriel Illouz, Thomas François


Abstract
In this paper, we present a study of MCQ aiming to define criteria in order to automatically select distractors. We are aiming to show that distractor editing follows rules like syntactic and semantic homogeneity according to associated answer, and the possibility to automatically identify this homogeneity. Manual analysis shows that homogeneity rule is respected to edit distractors and automatic analysis shows the possibility to reproduce these criteria. These ones can be used in future works to automatically select distractors, with the combination of other criteria.
Anthology ID:
L14-1544
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
4284–4291
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/692_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Van-Minh Pho, Thibault André, Anne-Laure Ligozat, Brigitte Grau, Gabriel Illouz, and Thomas François. 2014. Multiple Choice Question Corpus Analysis for Distractor Characterization. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 4284–4291, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Multiple Choice Question Corpus Analysis for Distractor Characterization (Pho et al., LREC 2014)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/692_Paper.pdf