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: []
paperswithcode_id: lc-quad-2-0
tags:
- knowledge-base-qa
dataset_info:
features:
- name: NNQT_question
dtype: string
- name: uid
dtype: int32
- name: subgraph
dtype: string
- name: template_index
dtype: int32
- name: question
dtype: string
- name: sparql_wikidata
dtype: string
- name: sparql_dbpedia18
dtype: string
- name: template
dtype: string
- name: paraphrased_question
dtype: string
splits:
- name: train
num_bytes: 16637751
num_examples: 19293
- name: test
num_bytes: 4067092
num_examples: 4781
download_size: 3959901
dataset_size: 20704843
Dataset Card for LC-QuAD 2.0
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
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: 3.87 MB
- Size of the generated dataset: 20.73 MB
- Total amount of disk used: 24.60 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
Languages
Dataset Structure
Data Instances
default
- 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 <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
: astring
feature.uid
: aint32
feature.subgraph
: astring
feature.template_index
: aint32
feature.question
: astring
feature.sparql_wikidata
: astring
feature.sparql_dbpedia18
: astring
feature.template
: astring
feature.paraphrased_question
: astring
feature.
Data Splits
name | train | test |
---|---|---|
default | 19293 | 4781 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
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
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.