AMUSE: Multilingual Semantic Parsing for Question Answering over Linked Data

The task of answering natural language questions over RDF data has received wide interest in recent years, in particular in the context of the series of QALD benchmarks. The task consists of mapping a natural language question to an executable form, e.g. SPARQL, so that answers from a given KB can be extracted.

Data and Resources

Cite this as

Sherzod Hakimov, Soufian Jebbara, Philipp Cimiano (2024). Dataset: AMUSE: Multilingual Semantic Parsing for Question Answering over Linked Data. https://doi.org/10.57702/o1kft9y0

DOI retrieved: December 16, 2024

Additional Info

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.1802.09296
Author Sherzod Hakimov
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Soufian Jebbara
Philipp Cimiano
Homepage https://github.com/ag-sc/AMUSE