albertvillanova
HF staff
Convert dataset sizes from base 2 to base 10 in the dataset card (#2)
831b6f8
metadata
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Compositional Freebase Questions
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- question-answering
- other
task_ids:
- open-domain-qa
- closed-domain-qa
paperswithcode_id: cfq
tags:
- compositionality
dataset_info:
- config_name: mcd1
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
- name: train
num_bytes: 37408806
num_examples: 95743
- name: test
num_bytes: 5446503
num_examples: 11968
download_size: 267599061
dataset_size: 42855309
- config_name: mcd2
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
- name: train
num_bytes: 39424657
num_examples: 95743
- name: test
num_bytes: 5314019
num_examples: 11968
download_size: 267599061
dataset_size: 44738676
- config_name: mcd3
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
- name: train
num_bytes: 38316345
num_examples: 95743
- name: test
num_bytes: 5244503
num_examples: 11968
download_size: 267599061
dataset_size: 43560848
- config_name: question_complexity_split
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
- name: train
num_bytes: 39989433
num_examples: 98999
- name: test
num_bytes: 5781561
num_examples: 10340
download_size: 267599061
dataset_size: 45770994
- config_name: question_pattern_split
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
- name: train
num_bytes: 41217350
num_examples: 95654
- name: test
num_bytes: 5179936
num_examples: 11909
download_size: 267599061
dataset_size: 46397286
- config_name: query_complexity_split
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
- name: train
num_bytes: 40270175
num_examples: 100654
- name: test
num_bytes: 5634924
num_examples: 9512
download_size: 267599061
dataset_size: 45905099
- config_name: query_pattern_split
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
- name: train
num_bytes: 40811284
num_examples: 94600
- name: test
num_bytes: 5268358
num_examples: 12589
download_size: 267599061
dataset_size: 46079642
- config_name: random_split
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
- name: train
num_bytes: 41279218
num_examples: 95744
- name: test
num_bytes: 5164923
num_examples: 11967
download_size: 267599061
dataset_size: 46444141
Dataset Card for "cfq"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://github.com/google-research/google-research/tree/master/cfq
- Repository: More Information Needed
- Paper: https://arxiv.org/abs/1912.09713
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 2.14 GB
- Size of the generated dataset: 362.07 MB
- Total amount of disk used: 2.50 GB
Dataset Summary
The Compositional Freebase Questions (CFQ) is a dataset that is specifically designed to measure compositional generalization. CFQ is a simple yet realistic, large dataset of natural language questions and answers that also provides for each question a corresponding SPARQL query against the Freebase knowledge base. This means that CFQ can also be used for semantic parsing.
Supported Tasks and Leaderboards
Languages
English (en
).
Dataset Structure
Data Instances
mcd1
- Size of downloaded dataset files: 267.60 MB
- Size of the generated dataset: 42.90 MB
- Total amount of disk used: 310.49 MB
An example of 'train' looks as follows.
{
'query': 'SELECT count(*) WHERE {\n?x0 a ns:people.person .\n?x0 ns:influence.influence_node.influenced M1 .\n?x0 ns:influence.influence_node.influenced M2 .\n?x0 ns:people.person.spouse_s/ns:people.marriage.spouse|ns:fictional_universe.fictional_character.married_to/ns:fictional_universe.marriage_of_fictional_characters.spouses ?x1 .\n?x1 a ns:film.cinematographer .\nFILTER ( ?x0 != ?x1 )\n}',
'question': 'Did a person marry a cinematographer , influence M1 , and influence M2'
}
mcd2
- Size of downloaded dataset files: 267.60 MB
- Size of the generated dataset: 44.77 MB
- Total amount of disk used: 312.38 MB
An example of 'train' looks as follows.
{
'query': 'SELECT count(*) WHERE {\n?x0 ns:people.person.parents|ns:fictional_universe.fictional_character.parents|ns:organization.organization.parent/ns:organization.organization_relationship.parent ?x1 .\n?x1 a ns:people.person .\nM1 ns:business.employer.employees/ns:business.employment_tenure.person ?x0 .\nM1 ns:business.employer.employees/ns:business.employment_tenure.person M2 .\nM1 ns:business.employer.employees/ns:business.employment_tenure.person M3 .\nM1 ns:business.employer.employees/ns:business.employment_tenure.person M4 .\nM5 ns:business.employer.employees/ns:business.employment_tenure.person ?x0 .\nM5 ns:business.employer.employees/ns:business.employment_tenure.person M2 .\nM5 ns:business.employer.employees/ns:business.employment_tenure.person M3 .\nM5 ns:business.employer.employees/ns:business.employment_tenure.person M4\n}',
'question': "Did M1 and M5 employ M2 , M3 , and M4 and employ a person 's child"
}
mcd3
- Size of downloaded dataset files: 267.60 MB
- Size of the generated dataset: 43.60 MB
- Total amount of disk used: 311.20 MB
An example of 'train' looks as follows.
{
"query": "SELECT /producer M0 . /director M0 . ",
"question": "Who produced and directed M0?"
}
query_complexity_split
- Size of downloaded dataset files: 267.60 MB
- Size of the generated dataset: 45.95 MB
- Total amount of disk used: 313.55 MB
An example of 'train' looks as follows.
{
"query": "SELECT /producer M0 . /director M0 . ",
"question": "Who produced and directed M0?"
}
query_pattern_split
- Size of downloaded dataset files: 267.60 MB
- Size of the generated dataset: 46.12 MB
- Total amount of disk used: 313.72 MB
An example of 'train' looks as follows.
{
"query": "SELECT /producer M0 . /director M0 . ",
"question": "Who produced and directed M0?"
}
Data Fields
The data fields are the same among all splits and configurations:
question
: astring
feature.query
: astring
feature.
Data Splits
name | train | test |
---|---|---|
mcd1 | 95743 | 11968 |
mcd2 | 95743 | 11968 |
mcd3 | 95743 | 11968 |
query_complexity_split | 100654 | 9512 |
query_pattern_split | 94600 | 12589 |
question_complexity_split | 98999 | 10340 |
question_pattern_split | 95654 | 11909 |
random_split | 95744 | 11967 |
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
Citation Information
@inproceedings{Keysers2020,
title={Measuring Compositional Generalization: A Comprehensive Method on
Realistic Data},
author={Daniel Keysers and Nathanael Sch"{a}rli and Nathan Scales and
Hylke Buisman and Daniel Furrer and Sergii Kashubin and
Nikola Momchev and Danila Sinopalnikov and Lukasz Stafiniak and
Tibor Tihon and Dmitry Tsarkov and Xiao Wang and Marc van Zee and
Olivier Bousquet},
booktitle={ICLR},
year={2020},
url={https://arxiv.org/abs/1912.09713.pdf},
}
Contributions
Thanks to @thomwolf, @patrickvonplaten, @lewtun, @brainshawn for adding this dataset.