Datasets:
Tasks:
Multiple Choice
Modalities:
Text
Formats:
parquet
Sub-tasks:
multiple-choice-qa
Size:
1K - 10K
License:
metadata
annotations_creators:
- other
language:
- ar
- bg
- de
- en
- es
- it
- ro
language_creators:
- found
license:
- unknown
multilinguality:
- multilingual
pretty_name: 'QA4MRE: Question Answering for Machine Reading Evaluation'
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- multiple-choice
task_ids:
- multiple-choice-qa
paperswithcode_id: null
Dataset Card for "qa4mre"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: http://nlp.uned.es/clef-qa/repository/qa4mre.php
- Repository: More Information Needed
- Paper: QA4MRE 2011-2013: Overview of Question Answering for Machine Reading Evaluation
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 5.24 MB
- Size of the generated dataset: 46.11 MB
- Total amount of disk used: 51.35 MB
Dataset Summary
QA4MRE dataset was created for the CLEF 2011/2012/2013 shared tasks to promote research in question answering and reading comprehension. The dataset contains a supporting passage and a set of questions corresponding to the passage. Multiple options for answers are provided for each question, of which only one is correct. The training and test datasets are available for the main track. Additional gold standard documents are available for two pilot studies: one on alzheimers data, and the other on entrance exams data.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
2011.main.DE
- Size of downloaded dataset files: 0.21 MB
- Size of the generated dataset: 1.67 MB
- Total amount of disk used: 1.88 MB
An example of 'train' looks as follows.
2011.main.EN
- Size of downloaded dataset files: 0.19 MB
- Size of the generated dataset: 1.50 MB
- Total amount of disk used: 1.69 MB
An example of 'train' looks as follows.
2011.main.ES
- Size of downloaded dataset files: 0.21 MB
- Size of the generated dataset: 1.62 MB
- Total amount of disk used: 1.82 MB
An example of 'train' looks as follows.
2011.main.IT
- Size of downloaded dataset files: 0.20 MB
- Size of the generated dataset: 1.59 MB
- Total amount of disk used: 1.79 MB
An example of 'train' looks as follows.
2011.main.RO
- Size of downloaded dataset files: 0.21 MB
- Size of the generated dataset: 1.66 MB
- Total amount of disk used: 1.87 MB
An example of 'train' looks as follows.
Data Fields
The data fields are the same among all splits.
2011.main.DE
topic_id: astringfeature.topic_name: astringfeature.test_id: astringfeature.document_id: astringfeature.document_str: astringfeature.question_id: astringfeature.question_str: astringfeature.answer_options: a dictionary feature containing:answer_id: astringfeature.answer_str: astringfeature.
correct_answer_id: astringfeature.correct_answer_str: astringfeature.
2011.main.EN
topic_id: astringfeature.topic_name: astringfeature.test_id: astringfeature.document_id: astringfeature.document_str: astringfeature.question_id: astringfeature.question_str: astringfeature.answer_options: a dictionary feature containing:answer_id: astringfeature.answer_str: astringfeature.
correct_answer_id: astringfeature.correct_answer_str: astringfeature.
2011.main.ES
topic_id: astringfeature.topic_name: astringfeature.test_id: astringfeature.document_id: astringfeature.document_str: astringfeature.question_id: astringfeature.question_str: astringfeature.answer_options: a dictionary feature containing:answer_id: astringfeature.answer_str: astringfeature.
correct_answer_id: astringfeature.correct_answer_str: astringfeature.
2011.main.IT
topic_id: astringfeature.topic_name: astringfeature.test_id: astringfeature.document_id: astringfeature.document_str: astringfeature.question_id: astringfeature.question_str: astringfeature.answer_options: a dictionary feature containing:answer_id: astringfeature.answer_str: astringfeature.
correct_answer_id: astringfeature.correct_answer_str: astringfeature.
2011.main.RO
topic_id: astringfeature.topic_name: astringfeature.test_id: astringfeature.document_id: astringfeature.document_str: astringfeature.question_id: astringfeature.question_str: astringfeature.answer_options: a dictionary feature containing:answer_id: astringfeature.answer_str: astringfeature.
correct_answer_id: astringfeature.correct_answer_str: astringfeature.
Data Splits
| name | train |
|---|---|
| 2011.main.DE | 120 |
| 2011.main.EN | 120 |
| 2011.main.ES | 120 |
| 2011.main.IT | 120 |
| 2011.main.RO | 120 |
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
@InProceedings{10.1007/978-3-642-40802-1_29,
author="Pe{\~{n}}as, Anselmo
and Hovy, Eduard
and Forner, Pamela
and Rodrigo, {\'A}lvaro
and Sutcliffe, Richard
and Morante, Roser",
editor="Forner, Pamela
and M{\"u}ller, Henning
and Paredes, Roberto
and Rosso, Paolo
and Stein, Benno",
title="QA4MRE 2011-2013: Overview of Question Answering for Machine Reading Evaluation",
booktitle="Information Access Evaluation. Multilinguality, Multimodality, and Visualization",
year="2013",
publisher="Springer Berlin Heidelberg",
address="Berlin, Heidelberg",
pages="303--320",
isbn="978-3-642-40802-1"
}
Contributions
Thanks to @patrickvonplaten, @albertvillanova, @mariamabarham, @thomwolf for adding this dataset.