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  Knowledge Questions from Knowledge Graphs

Seyler, D., Yahya, M., & Berberich, K. (2016). Knowledge Questions from Knowledge Graphs. Retrieved from http://arxiv.org/abs/1610.09935.

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arXiv:1610.09935.pdf (Preprint), 593KB
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 Creators:
Seyler, Dominic1, Author           
Yahya, Mohamed2, Author           
Berberich, Klaus2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

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Free keywords: Computer Science, Computation and Language, cs.CL
 Abstract: We address the novel problem of automatically generating quiz-style knowledge questions from a knowledge graph such as DBpedia. Questions of this kind have ample applications, for instance, to educate users about or to evaluate their knowledge in a specific domain. To solve the problem, we propose an end-to-end approach. The approach first selects a named entity from the knowledge graph as an answer. It then generates a structured triple-pattern query, which yields the answer as its sole result. If a multiple-choice question is desired, the approach selects alternative answer options. Finally, our approach uses a template-based method to verbalize the structured query and yield a natural language question. A key challenge is estimating how difficult the generated question is to human users. To do this, we make use of historical data from the Jeopardy! quiz show and a semantically annotated Web-scale document collection, engineer suitable features, and train a logistic regression classifier to predict question difficulty. Experiments demonstrate the viability of our overall approach.

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Language(s): eng - English
 Dates: 2016-10-312016-11-012016
 Publication Status: Published online
 Pages: 9 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: arXiv: 1610.09935
URI: http://arxiv.org/abs/1610.09935
BibTex Citekey: Seyler1610.09935
 Degree: -

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