README.md

metadata

annotations_creators:
  - crowdsourced
language:
  - en
language_creators:
  - found
license:
  - cc-by-4.0
multilinguality:
  - monolingual
pretty_name: Quoref
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - question-answering
task_ids: []
paperswithcode_id: quoref
tags:
  - coreference-resolution
dataset_info:
  features:
    - name: id
      dtype: string
    - name: question
      dtype: string
    - name: context
      dtype: string
    - name: title
      dtype: string
    - name: url
      dtype: string
    - name: answers
      sequence:
        - name: answer_start
          dtype: int32
        - name: text
          dtype: string
  splits:
    - name: train
      num_bytes: 44377729
      num_examples: 19399
    - name: validation
      num_bytes: 5442031
      num_examples: 2418
  download_size: 5078438
  dataset_size: 49819760

Dataset Card for "quoref"

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://allenai.org/data/quoref
• Repository: More Information Needed
• Paper: Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 5.08 MB
• Size of the generated dataset: 49.82 MB
• Total amount of disk used: 54.90 MB

Dataset Summary

Quoref is a QA dataset which tests the coreferential reasoning capability of reading comprehension systems. In this span-selection benchmark containing 24K questions over 4.7K paragraphs from Wikipedia, a system must resolve hard coreferences before selecting the appropriate span(s) in the paragraphs for answering questions.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 5.08 MB
• Size of the generated dataset: 49.82 MB
• Total amount of disk used: 54.90 MB

An example of 'validation' looks as follows.

This example was too long and was cropped:

{
    "answers": {
        "answer_start": [1633],
        "text": ["Frankie"]
    },
    "context": "\"Frankie Bono, a mentally disturbed hitman from Cleveland, comes back to his hometown in New York City during Christmas week to ...",
    "id": "bfc3b34d6b7e73c0bd82a009db12e9ce196b53e6",
    "question": "What is the first name of the person who has until New Year's Eve to perform a hit?",
    "title": "Blast of Silence",
    "url": "https://en.wikipedia.org/wiki/Blast_of_Silence"
}

Data Fields

The data fields are the same among all splits.

default

• id: a string feature.
• question: a string feature.
• context: a string feature.
• title: a string feature.
• url: a string feature.
• answers: a dictionary feature containing:
  • answer_start: a int32 feature.
  • text: a string feature.

Data Splits

name	train	validation
default	19399	2418

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

@article{allenai:quoref,
      author    = {Pradeep Dasigi and Nelson F. Liu and Ana Marasovic and Noah A. Smith and  Matt Gardner},
      title     = {Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning},
      journal   = {arXiv:1908.05803v2 },
      year      = {2019},
}

Contributions

Thanks to @lewtun, @patrickvonplaten, @thomwolf for adding this dataset.