albertvillanova
HF staff
Convert dataset sizes from base 2 to base 10 in the dataset card (#1)
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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 Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
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
Languages
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: astringfeature.question: astringfeature.context: astringfeature.title: astringfeature.url: astringfeature.answers: a dictionary feature containing:answer_start: aint32feature.text: astringfeature.
Data Splits
| name | train | validation |
|---|---|---|
| default | 19399 | 2418 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
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
@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.