README.md

metadata

annotations_creators:
  - crowdsourced
language:
  - en
language_creators:
  - found
license:
  - cc-by-3.0
multilinguality:
  - monolingual
pretty_name: 'LC-QuAD 2.0: Large-scale Complex Question Answering Dataset'
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - question-answering
task_ids:
  - question-answering-other-knowledge-base-qa
paperswithcode_id: lc-quad-2-0

Dataset Card for LC-QuAD 2.0

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: http://lc-quad.sda.tech/
• Repository: https://github.com/AskNowQA/LC-QuAD2.0
• Paper: LC-QuAD 2.0: A Large Dataset for Complex Question Answering over Wikidata and DBpedia
• Point of Contact: Mohnish Dubey or Mohnish Dubey
• Size of downloaded dataset files: 3.69 MB
• Size of the generated dataset: 19.77 MB
• Total amount of disk used: 23.46 MB

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

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 3.69 MB
• Size of the generated dataset: 19.77 MB
• Total amount of disk used: 23.46 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 <http://www.w3.org/1999/02/22-rdf-syntax-ns#subject> <http://wikidata.dbpedia.org/resou...",
    "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.

default

• 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

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

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

Citation Information

@inproceedings{dubey2017lc2,
   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)},
   year={2019},
   organization={Springer}
}

Contributions

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