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---
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:
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num_examples: 95743
- name: test
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num_examples: 11968
download_size: 267599061
dataset_size: 44738676
- config_name: mcd3
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
- name: train
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num_examples: 95743
- name: test
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num_examples: 11968
download_size: 267599061
dataset_size: 43560848
- config_name: question_complexity_split
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
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- name: test
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num_examples: 10340
download_size: 267599061
dataset_size: 45770994
- config_name: question_pattern_split
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
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num_examples: 95654
- name: test
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num_examples: 11909
download_size: 267599061
dataset_size: 46397286
- config_name: query_complexity_split
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
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num_examples: 100654
- name: test
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num_examples: 9512
download_size: 267599061
dataset_size: 45905099
- config_name: query_pattern_split
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
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num_examples: 94600
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num_examples: 12589
download_size: 267599061
dataset_size: 46079642
- config_name: random_split
features:
- name: question
dtype: string
- name: query
dtype: string
splits:
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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-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** [https://github.com/google-research/google-research/tree/master/cfq](https://github.com/google-research/google-research/tree/master/cfq)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** https://arxiv.org/abs/1912.09713
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 2041.62 MB
- **Size of the generated dataset:** 345.30 MB
- **Total amount of disk used:** 2386.92 MB
### 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
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Languages
English (`en`).
## Dataset Structure
### Data Instances
#### mcd1
- **Size of downloaded dataset files:** 255.20 MB
- **Size of the generated dataset:** 40.91 MB
- **Total amount of disk used:** 296.11 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:** 255.20 MB
- **Size of the generated dataset:** 42.70 MB
- **Total amount of disk used:** 297.91 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:** 255.20 MB
- **Size of the generated dataset:** 41.58 MB
- **Total amount of disk used:** 296.78 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:** 255.20 MB
- **Size of the generated dataset:** 43.82 MB
- **Total amount of disk used:** 299.02 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:** 255.20 MB
- **Size of the generated dataset:** 43.98 MB
- **Total amount of disk used:** 299.19 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`: a `string` feature.
- `query`: a `string` 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
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
#### Who are the source language producers?
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Annotations
#### Annotation process
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
#### Who are the annotators?
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Personal and Sensitive Information
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Discussion of Biases
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Other Known Limitations
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
## Additional Information
### Dataset Curators
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Licensing Information
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### 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](https://github.com/thomwolf), [@patrickvonplaten](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun), [@brainshawn](https://github.com/brainshawn) for adding this dataset. |