YAML Metadata Warning:The task_categories "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

Dataset Card for "break_data"

Dataset Summary

Break is a human annotated dataset of natural language questions and their Question Decomposition Meaning Representations (QDMRs). Break consists of 83,978 examples sampled from 10 question answering datasets over text, images and databases. This repository contains the Break dataset along with information on the exact data format.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

QDMR

Size of downloaded dataset files: 15.97 MB
Size of the generated dataset: 15.93 MB
Total amount of disk used: 31.90 MB

An example of 'validation' looks as follows.

{
    "decomposition": "return flights ;return #1 from  denver ;return #2 to philadelphia ;return #3 if  available",
    "operators": "['select', 'filter', 'filter', 'filter']",
    "question_id": "ATIS_dev_0",
    "question_text": "what flights are available tomorrow from denver to philadelphia ",
    "split": "dev"
}

QDMR-high-level

Size of downloaded dataset files: 15.97 MB
Size of the generated dataset: 6.54 MB
Total amount of disk used: 22.51 MB

An example of 'train' looks as follows.

{
    "decomposition": "return ground transportation ;return #1 which  is  available ;return #2 from  the pittsburgh airport ;return #3 to downtown ;return the cost of #4",
    "operators": "['select', 'filter', 'filter', 'filter', 'project']",
    "question_id": "ATIS_dev_102",
    "question_text": "what ground transportation is available from the pittsburgh airport to downtown and how much does it cost ",
    "split": "dev"
}

QDMR-high-level-lexicon

Size of downloaded dataset files: 15.97 MB
Size of the generated dataset: 31.64 MB
Total amount of disk used: 47.61 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "allowed_tokens": "\"['higher than', 'same as', 'what ', 'and ', 'than ', 'at most', 'he', 'distinct', 'House', 'two', 'at least', 'or ', 'date', 'o...",
    "source": "What office, also held by a member of the Maine House of Representatives, did James K. Polk hold before he was president?"
}

QDMR-lexicon

Size of downloaded dataset files: 15.97 MB
Size of the generated dataset: 77.19 MB
Total amount of disk used: 93.16 MB

An example of 'validation' looks as follows.

This example was too long and was cropped:

{
    "allowed_tokens": "\"['higher than', 'same as', 'what ', 'and ', 'than ', 'at most', 'distinct', 'two', 'at least', 'or ', 'date', 'on ', '@@14@@', ...",
    "source": "what flights are available tomorrow from denver to philadelphia "
}

logical-forms

Size of downloaded dataset files: 15.97 MB
Size of the generated dataset: 24.25 MB
Total amount of disk used: 40.22 MB

An example of 'train' looks as follows.

{
    "decomposition": "return ground transportation ;return #1 which  is  available ;return #2 from  the pittsburgh airport ;return #3 to downtown ;return the cost of #4",
    "operators": "['select', 'filter', 'filter', 'filter', 'project']",
    "program": "some program",
    "question_id": "ATIS_dev_102",
    "question_text": "what ground transportation is available from the pittsburgh airport to downtown and how much does it cost ",
    "split": "dev"
}

Data Fields

The data fields are the same among all splits.

QDMR

question_id: a string feature.
question_text: a string feature.
decomposition: a string feature.
operators: a string feature.
split: a string feature.

QDMR-high-level

question_id: a string feature.
question_text: a string feature.
decomposition: a string feature.
operators: a string feature.
split: a string feature.

QDMR-high-level-lexicon

source: a string feature.
allowed_tokens: a string feature.

QDMR-lexicon

source: a string feature.
allowed_tokens: a string feature.

logical-forms

question_id: a string feature.
question_text: a string feature.
decomposition: a string feature.
operators: a string feature.
split: a string feature.
program: a string feature.

Data Splits

name	train	validation	test
QDMR	44321	7760	8069
QDMR-high-level	17503	3130	3195
QDMR-high-level-lexicon	17503	3130	3195
QDMR-lexicon	44321	7760	8069
logical-forms	44098	7719	8006

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

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

@article{Wolfson2020Break,
  title={Break It Down: A Question Understanding Benchmark},
  author={Wolfson, Tomer and Geva, Mor and Gupta, Ankit and Gardner, Matt and Goldberg, Yoav and Deutch, Daniel and Berant, Jonathan},
  journal={Transactions of the Association for Computational Linguistics},
  year={2020},
}