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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.

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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

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Additional Info

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