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Dataset Card for LC-QuAD 2.0

Dataset Summary

LC-QuAD 2.0 is a Large Question Answering dataset with 30,000 pairs of question and its corresponding SPARQL query. The target knowledge base is Wikidata and DBpedia, specifically the 2018 version. Please see our paper for details about the dataset creation process and framework.

Supported Tasks and Leaderboards

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Dataset Structure

Data Instances


  • Size of downloaded dataset files: 3.87 MB
  • Size of the generated dataset: 20.73 MB
  • Total amount of disk used: 24.60 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

    "NNQT_question": "What is the {periodical literature} for {mouthpiece} of {Delta Air Lines}",
    "paraphrased_question": "What is Delta Air Line's periodical literature mouthpiece?",
    "question": "What periodical literature does Delta Air Lines use as a moutpiece?",
    "sparql_dbpedia18": "\"select distinct ?obj where { ?statement <> <",
    "sparql_wikidata": " select distinct ?obj where { wd:Q188920 wdt:P2813 ?obj . ?obj wdt:P31 wd:Q1002697 } ",
    "subgraph": "simple question right",
    "template": " <S P ?O ; ?O instanceOf Type>",
    "template_index": 65,
    "uid": 19719

Data Fields

The data fields are the same among all splits.


  • NNQT_question: a string feature.
  • uid: a int32 feature.
  • subgraph: a string feature.
  • template_index: a int32 feature.
  • question: a string feature.
  • sparql_wikidata: a string feature.
  • sparql_dbpedia18: a string feature.
  • template: a string feature.
  • paraphrased_question: a string feature.

Data Splits

name train test
default 19293 4781

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

LC-QuAD 2.0 is licensed under a Creative Commons Attribution 3.0 Unported License.

Citation Information

   title={LC-QuAD 2.0: A Large Dataset for Complex Question Answering over Wikidata and DBpedia},
   author={Dubey, Mohnish and Banerjee, Debayan and Abdelkawi, Abdelrahman and Lehmann, Jens},
   booktitle={Proceedings of the 18th International Semantic Web Conference (ISWC)},


Thanks to @lewtun, @thomwolf, @patrickvonplaten for adding this dataset.

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