README.md

metadata

annotations_creators:
  - no-annotation
language_creators:
  - expert-generated
language:
  - en
license:
  - cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - 100K<n<1M
source_datasets:
  - original
task_categories:
  - question-answering
  - other
task_ids:
  - open-domain-qa
  - closed-domain-qa
paperswithcode_id: cfq
pretty_name: Compositional Freebase Questions
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: 8570962
    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: 8867866
    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: 8578142
    dataset_size: 43560848
  - 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: 9303588
    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: 9387759
    dataset_size: 46079642
  - 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: 9255771
    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: 9482990
    dataset_size: 46397286
  - 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: 9533853
    dataset_size: 46444141
configs:
  - config_name: mcd1
    data_files:
      - split: train
        path: mcd1/train-*
      - split: test
        path: mcd1/test-*
  - config_name: mcd2
    data_files:
      - split: train
        path: mcd2/train-*
      - split: test
        path: mcd2/test-*
  - config_name: mcd3
    data_files:
      - split: train
        path: mcd3/train-*
      - split: test
        path: mcd3/test-*
  - config_name: query_complexity_split
    data_files:
      - split: train
        path: query_complexity_split/train-*
      - split: test
        path: query_complexity_split/test-*
  - config_name: query_pattern_split
    data_files:
      - split: train
        path: query_pattern_split/train-*
      - split: test
        path: query_pattern_split/test-*
  - config_name: question_complexity_split
    data_files:
      - split: train
        path: question_complexity_split/train-*
      - split: test
        path: question_complexity_split/test-*
  - config_name: question_pattern_split
    data_files:
      - split: train
        path: question_pattern_split/train-*
      - split: test
        path: question_pattern_split/test-*
  - config_name: random_split
    data_files:
      - split: train
        path: random_split/train-*
      - split: test
        path: random_split/test-*

Dataset Card for "cfq"

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: 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

More Information Needed

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: 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

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

More Information Needed

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.