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Data Characteristics
| Current Version | 1.0 |
| Total Questions | 5000 |
| Unique Templates | 38 |
| Entities Covered | 5042 |
| Predicates Covered | 615 |
Contact Us
In case you find any bug in our framework, or any issue with our dataset, please inform us on Issues Page.
Contact priyansh.trivedi@uni-bonn.de for anything regarding the dataset.What is LC-QuAD?
The aim of LC-QuAD is to make a large dataset for Question Answering (QA) over structured data (in RDF format) available. It consists of 5000 pairs of natural language question and the corresponding SPARQL query. In order to create the dataset, we used a set of typical query templates and then converted seed entities in the RDF graph to a normalised natural natural question structure (NNQS). This was then transformed to natural language questions with different lexical and syntactical variations by English native speakers. Please see our paper for more details.
Examples
Q: What are the mascots of the teams participating in the turkish handball super league?
Q: Which band has Joe Hahn and Chester Bennington?
SELECT DISTINCT ?uri WHERE {
?uri dbp:currentMembers dbr:Joe_Hahn .
?uri dbp:currentMembers dbr:Chester_Bennington
}
?uri dbp:currentMembers dbr:Joe_Hahn .
?uri dbp:currentMembers dbr:Chester_Bennington
}
Q: List down the movies whose music composers have won the BAFTA Award for Best Film Music ?
SELECT DISTINCT ?uri WHERE {
?x dbp:award dbr:BAFTA_Award_for_Best_Film_Music .
?uri dbp:musicComposer ?x
}
?x dbp:award dbr:BAFTA_Award_for_Best_Film_Music .
?uri dbp:musicComposer ?x
}
Documentation & Usage Guides
The documentation of the project will soon be made available on our repository's wiki.
We're working round the clock to get it up!
Every data item in the dataset consists of the following fields:
{
template_id: "Every unique SPARQL template has a different ID.",
sparql_template: "A query where resources in the triple pattern are replaced with placeholders.",
sparql_query: "Valid SPARQL query generated by using the triples in subgraphs to fill the placeholder
resources in SPARQL Templates.",
verbalized_question: "The automatically verbalized equivalent of the SPARQL Query.",
corrected_question: "Human corrected version of the verbalized question.",
_id: "Unique ID generated for every data node."
}
