AutoSPARQL: Convert a natural language expression to a SPARQL query

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The underlying idea of the project is to convert a natural language expression to a SPARQL query, which can then retrieve the answer of a question from a given triple store.

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The aim of AutoSPARQL is to provide robust question answering over RDF data by combining methods from several research areas, such as:

  • natural language processing for creating sophisticated semantic representations of questions
  • inductive active learning for incorporating user feedback
  • results of the BOA project

The underlying idea is to convert a natural language expression to a SPARQL query, which can then retrieve the answer of a question from a given triple store.

Papers

Sourcecode

  • main (is not actively maintained anymore)
  • machine learning algorithms in DL-Learner
  • natural language patterns in BOA

Project Team

Publications

by (Editors: ) [BibTex of ]

News

AKSW Colloquium, 23.01.2017, Automatic Mappings of Tables to Knowledge Graphs and Open Table Extraction ( 2017-01-20T14:02:35+01:00 by Ivan Ermilov)

2017-01-20T14:02:35+01:00 by Ivan Ermilov

Automatic Mappings of Tables to Knowledge Graphs and Open Table Extraction On the upcoming colloquium on 23.01. Read more about "AKSW Colloquium, 23.01.2017, Automatic Mappings of Tables to Knowledge Graphs and Open Table Extraction"

PRESS RELEASE: “HOBBIT so far.” is now available ( 2017-01-09T14:22:29+01:00 by Sandra Bartsch)

2017-01-09T14:22:29+01:00 by Sandra Bartsch

The latest release informs about the conferences our team attended in 2016 as well as about the published blogposts. Read more about "PRESS RELEASE: “HOBBIT so far.” is now available"

4th Big Data Europe Plenary at Leipzig University ( 2016-12-16T14:33:41+01:00 by Sandra Bartsch)

2016-12-16T14:33:41+01:00 by Sandra Bartsch

The meeting, hosted by our partner InfAI e. V., took place on the 14th to the 15th of December at the University of Leipzig. Read more about "4th Big Data Europe Plenary at Leipzig University"

SANSA 0.1 (Semantic Analytics Stack) Released ( 2016-12-09T15:41:04+01:00 by Dr. Jens Lehmann)

2016-12-09T15:41:04+01:00 by Dr. Jens Lehmann

Dear all, The Smart Data Analytics group /AKSW are very happy to announce SANSA 0.1 – the initial release of the Scalable Semantic Analytics Stack. Read more about "SANSA 0.1 (Semantic Analytics Stack) Released"

AKSW wins award for Best Resources Paper at ISWC 2016 in Japan ( 2016-12-09T15:05:00+01:00 by Sandra Bartsch)

2016-12-09T15:05:00+01:00 by Sandra Bartsch

Our paper, “LODStats: The Data Web Census Dataset”, won the award for Best Resources Paper at the recent conference in Kobe/Japan, which was the premier international forum for Semantic Web and Linked Data Community. Read more about "AKSW wins award for Best Resources Paper at ISWC 2016 in Japan"