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| + | |Author=Denny Vrandecic | ||
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| + | |Author=Elena Simperl | ||
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| − | |Title= | + | |Title=SPARTIQULATION: Verbalizing SPARQL queries |
|Year=2012 | |Year=2012 | ||
| − | |Booktitle= | + | |Month=Mai |
| + | |Booktitle=Proceedings of the 11th Extended Semantic Web Conference, | ||
|Publisher=Springer | |Publisher=Springer | ||
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{{Publikation Details | {{Publikation Details | ||
| + | |Abstract=Much research has been done to combine the fields of Databases and Natural Language Processing. While many works focus on the problem of deriving a structured query for a given natural language question, the problem of query verbalization - translating a structured query into natural language - is less explored. In this work we describe our approach to verbalizing SPARQL queries in order to create natural language expressions that are readable and understandable by the human day-to-day user. These expressions are helpful when having search engines generate SPARQL queries for user-provided natural language questions or keywords and enable the user to check whether the right question has been understood. While our approach enables verbalization of only a subset of SPARQL 1.1, this subset applies to 85% of the 209 queries in our training set. These observations are based on a corpus of SPARQL queries consisting of datasets from the QALD-1 challenge and the ILD2012 challenge. | ||
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| + | (This is an extended version of the paper ...) | ||
| + | |Download=ESWC2012-PP SPARQL.pdf, | ||
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|Forschungsgruppe=Wissensmanagement | |Forschungsgruppe=Wissensmanagement | ||
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Version vom 5. August 2014, 10:02 Uhr
SPARTIQULATION: Verbalizing SPARQL queries
SPARTIQULATION: Verbalizing SPARQL queries
Published: 2012
Mai
Buchtitel: Proceedings of the 11th Extended Semantic Web Conference,
Verlag: Springer
Referierte Veröffentlichung
Kurzfassung
Much research has been done to combine the fields of Databases and Natural Language Processing. While many works focus on the problem of deriving a structured query for a given natural language question, the problem of query verbalization - translating a structured query into natural language - is less explored. In this work we describe our approach to verbalizing SPARQL queries in order to create natural language expressions that are readable and understandable by the human day-to-day user. These expressions are helpful when having search engines generate SPARQL queries for user-provided natural language questions or keywords and enable the user to check whether the right question has been understood. While our approach enables verbalization of only a subset of SPARQL 1.1, this subset applies to 85% of the 209 queries in our training set. These observations are based on a corpus of SPARQL queries consisting of datasets from the QALD-1 challenge and the ILD2012 challenge.
(This is an extended version of the paper ...)
Download: Media:ESWC2012-PP SPARQL.pdf