Automatic Question Generation from Sentences

Husam Ali, Yllias Chali, Sadid A. Hasan


Abstract
Question Generation (QG) and Question Answering (QA) are some of the many challenges for natural language understanding and interfaces. As humans need to ask good questions, the potential benefits from automated QG systems may assist them in meeting useful inquiry needs. In this paper, we consider an automatic Sentence-to-Question generation task, where given a sentence, the Question Generation (QG) system generates a set of questions for which the sentence contains, implies, or needs answers. To facilitate the question generation task, we build elementary sentences from the input complex sentences using a syntactic parser. A named entity recognizer and a part of speech tagger are applied on each of these sentences to encode necessary information.We classify the sentences based on their subject, verb, object and preposition for determining the possible type of questions to be generated. We use the TREC-2007 (Question Answering Track) dataset for our experiments and evaluation.
Anthology ID:
2010.jeptalnrecital-court.36
Volume:
Actes de la 17e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts
Month:
July
Year:
2010
Address:
Montréal, Canada
Venue:
JEP/TALN/RECITAL
SIG:
Publisher:
ATALA
Note:
Pages:
213–218
Language:
URL:
https://aclanthology.org/2010.jeptalnrecital-court.36
DOI:
Bibkey:
Cite (ACL):
Husam Ali, Yllias Chali, and Sadid A. Hasan. 2010. Automatic Question Generation from Sentences. In Actes de la 17e conférence sur le Traitement Automatique des Langues Naturelles. Articles courts, pages 213–218, Montréal, Canada. ATALA.
Cite (Informal):
Automatic Question Generation from Sentences (Ali et al., JEP/TALN/RECITAL 2010)
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PDF:
https://aclanthology.org/2010.jeptalnrecital-court.36.pdf