Question Generation based on Lexico-Syntactic Patterns Learned from the Web

Authors

  • Sergio Curto Spoken Language Systems Laboratory - L2F/INESC-ID
  • Ana Cristina Mendes Spoken Language Systems Laboratory - L2F/INESC-ID
  • Luisa Coheur Spoken Language Systems Laboratory - L2F/INESC-ID

DOI:

https://doi.org/10.5087/dad.2012.207

Abstract

THE MENTOR automatically generates multiple-choice tests from a given text. This tool aims at supporting the dialogue system of the FalaComigo project, as one of FalaComigo's goals is the interaction with tourists through questions/answers and quizzes about their visit. In a minimally supervised learning process and by leveraging the redundancy and linguistic variability of the Web, THE MENTOR learns lexico-syntactic patterns using a set of question/answer seeds. Afterward, these patterns are used to match the sentences from which new questions (and answers) can be generated. Finally, several ï¬lters are applied in order to discard low quality items. In this paper we detail the question generation task as performed by T- Mand evaluate its performance.

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Published

2012-03-16

Issue

Section

Articles