A consolidated dataset for knowledge-based question generation using predicate mapping of linked data

Melly, Johanna (Cortexia S.A., Châtel-Saint-Denis, Switzerland) ; Luthier, Gabriel (School of Management and Engineering Vaud, HES-SO // University of Applied Sciences Western Switzerland) ; Popescu-Melis, Andrei (School of Management and Engineering Vaud, HES-SO // University of Applied Sciences Western Switzerland)

In this paper, we present the ForwardQuestions data set, made of human-generated questions related to knowledge triples. This data setresults from the conversion and merger of the existing SimpleDBPediaQA and SimpleQuestionsWikidata data sets, including the mapping of predicates from DBPedia to Wikidata, and the selection of ‘forward’ questions as opposed to ‘backward’ ones. The new data set can be used to generate novel questions given an unseen Wikidata triple, by replacing the subjects of existing questions with the new one and then selecting the best candidate questions using semantic and syntactic criteria. Evaluation results indicate that the question generation method using ForwardQuestions improves the quality of questions by about 20% with respect to a baseline not using ranking criteria.


Note: As the LREC 2020 conference has been cancelled, due to the Covid-19 outbreak, so has the ISA-16 workshop. The workshop proceedings are however published according to the original schedule.


Keywords:
Conference Type:
full paper
Faculty:
Ingénierie et Architecture
School:
HEIG-VD
Institute:
IICT - Institut des Technologies de l'Information et de la Communication
Publisher:
Marseille, France, 12 May 2020
Date:
2020-05
Marseille, France
12 May 2020
Pagination:
8 p.
Published in:
Proceedings of the 16th Joint ACL - ISO Workshop on Interoperable Semantic Annotation (ISA-16), 12 May 2020, Marseille France
ISBN:
978-90-74029-39-1
External resources:
Appears in Collection:



 Record created 2020-06-23, last modified 2020-06-25

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