qa_zre / README.md
system's picture
system HF staff
Update files from the datasets library (from 1.7.0)
5ef2261
|
raw
history blame
5.98 kB
metadata
paperswithcode_id: null

Dataset Card for "qa_zre"

Table of Contents

Dataset Description

Dataset Summary

A dataset reducing relation extraction to simple reading comprehension questions

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

default

  • Size of downloaded dataset files: 492.15 MB
  • Size of the generated dataset: 1989.22 MB
  • Total amount of disk used: 2481.37 MB

An example of 'validation' looks as follows.

{
    "answers": [],
    "context": "answer",
    "question": "What is XXX in this question?",
    "relation": "relation_name",
    "subject": "Some entity Here is a bit of context which will explain the question in some way"
}

Data Fields

The data fields are the same among all splits.

default

  • relation: a string feature.
  • question: a string feature.
  • subject: a string feature.
  • context: a string feature.
  • answers: a list of string features.

Data Splits

name train validation test
default 8400000 6000 120000

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{levy-etal-2017-zero,
    title = "Zero-Shot Relation Extraction via Reading Comprehension",
    author = "Levy, Omer  and
      Seo, Minjoon  and
      Choi, Eunsol  and
      Zettlemoyer, Luke",
    booktitle = "Proceedings of the 21st Conference on Computational Natural Language Learning ({C}o{NLL} 2017)",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/K17-1034",
    doi = "10.18653/v1/K17-1034",
    pages = "333--342",
}

Contributions

Thanks to @thomwolf, @lhoestq, @ghomasHudson, @lewtun for adding this dataset.