Natural language questions for the web of data

Authors:
Mohamed Yahya;Klaus Berberich;Shady Elbassuoni;Maya Ramanath;Volker Tresp;Gerhard Weikum
Affiliations:
Max Planck Institute for Informatics, Germany;Max Planck Institute for Informatics, Germany;Qatar Computing Research Institute;IIT-Delhi, India;Siemens AG, Corporate Technology, Munich, Germany;Max Planck Institute for Informatics, Germany
Venue:
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Year:
2012

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Abstract

The Linked Data initiative comprises structured databases in the Semantic-Web data model RDF. Exploring this heterogeneous data by structured query languages is tedious and error-prone even for skilled users. To ease the task, this paper presents a methodology for translating natural language questions into structured SPARQL queries over linked-data sources. Our method is based on an integer linear program to solve several disambiguation tasks jointly: the segmentation of questions into phrases; the mapping of phrases to semantic entities, classes, and relations; and the construction of SPARQL triple patterns. Our solution harnesses the rich type system provided by knowledge bases in the web of linked data, to constrain our semantic-coherence objective function. We present experiments on both the question translation and the resulting query answering.