Datasets:
annotations_creators:
- other
language_creators:
- found
language:
- ar
- bg
- de
- en
- es
- it
- ro
license:
- unknown
multilinguality:
- multilingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- multiple-choice
task_ids:
- multiple-choice-qa
pretty_name: 'QA4MRE: Question Answering for Machine Reading Evaluation'
dataset_info:
- config_name: 2011.main.DE
features:
- name: topic_id
dtype: string
- name: topic_name
dtype: string
- name: test_id
dtype: string
- name: document_id
dtype: string
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dtype: string
- name: question_id
dtype: string
- name: question_str
dtype: string
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sequence:
- name: answer_id
dtype: string
- name: answer_str
dtype: string
- name: correct_answer_id
dtype: string
- name: correct_answer_str
dtype: string
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- name: question_str
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- name: answer_id
dtype: string
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dtype: string
- name: correct_answer_id
dtype: string
- name: correct_answer_str
dtype: string
splits:
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download_size: 115284
dataset_size: 1569624
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features:
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- name: test_id
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dtype: string
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- name: answer_id
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- name: correct_answer_id
dtype: string
- name: correct_answer_str
dtype: string
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num_examples: 120
download_size: 125016
dataset_size: 1694408
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features:
- name: topic_id
dtype: string
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- name: test_id
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features:
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splits:
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num_examples: 120
download_size: 129859
dataset_size: 1740367
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features:
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- name: correct_answer_str
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splits:
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num_examples: 160
download_size: 168781
dataset_size: 2710604
- config_name: 2012.main.BG
features:
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splits:
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download_size: 203734
dataset_size: 3454163
- config_name: 2012.main.DE
features:
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splits:
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download_size: 158289
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- config_name: 2012.main.EN
features:
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splits:
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num_examples: 160
download_size: 137169
dataset_size: 1757534
- config_name: 2012.main.ES
features:
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splits:
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download_size: 152867
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- config_name: 2012.main.IT
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splits:
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num_examples: 160
download_size: 156976
dataset_size: 2071658
- config_name: 2012.main.RO
features:
- name: topic_id
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dtype: string
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dtype: string
- name: question_str
dtype: string
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sequence:
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dtype: string
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dtype: string
- name: correct_answer_str
dtype: string
splits:
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num_examples: 160
download_size: 157140
dataset_size: 2074878
- config_name: 2013.alzheimers.EN
features:
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dtype: string
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dtype: string
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dtype: string
splits:
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num_examples: 40
download_size: 274413
dataset_size: 2614812
- config_name: 2013.entrance_exam.EN
features:
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splits:
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num_examples: 46
download_size: 54598
dataset_size: 180827
- config_name: 2013.main.AR
features:
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dtype: string
splits:
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num_examples: 284
download_size: 155246
dataset_size: 4180927
- config_name: 2013.main.BG
features:
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dtype: string
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dtype: string
- name: answer_options
sequence:
- name: answer_id
dtype: string
- name: answer_str
dtype: string
- name: correct_answer_id
dtype: string
- name: correct_answer_str
dtype: string
splits:
- name: train
num_bytes: 5403194
num_examples: 284
download_size: 191476
dataset_size: 5403194
- config_name: 2013.main.EN
features:
- name: topic_id
dtype: string
- name: topic_name
dtype: string
- name: test_id
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dtype: string
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sequence:
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dtype: string
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dtype: string
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dtype: string
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dtype: string
splits:
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num_examples: 284
download_size: 134883
dataset_size: 2887814
- config_name: 2013.main.ES
features:
- name: topic_id
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dtype: string
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- config_name: 2013.main.RO
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: string
- name: correct_answer_str
dtype: string
splits:
- name: train
num_bytes: 3362997
num_examples: 284
download_size: 154236
dataset_size: 3362997
configs:
- config_name: 2011.main.DE
data_files:
- split: train
path: 2011.main.DE/train-*
- config_name: 2011.main.EN
data_files:
- split: train
path: 2011.main.EN/train-*
- config_name: 2011.main.ES
data_files:
- split: train
path: 2011.main.ES/train-*
- config_name: 2011.main.IT
data_files:
- split: train
path: 2011.main.IT/train-*
- config_name: 2011.main.RO
data_files:
- split: train
path: 2011.main.RO/train-*
- config_name: 2012.alzheimers.EN
data_files:
- split: train
path: 2012.alzheimers.EN/train-*
- config_name: 2012.main.AR
data_files:
- split: train
path: 2012.main.AR/train-*
- config_name: 2012.main.BG
data_files:
- split: train
path: 2012.main.BG/train-*
- config_name: 2012.main.DE
data_files:
- split: train
path: 2012.main.DE/train-*
- config_name: 2012.main.EN
data_files:
- split: train
path: 2012.main.EN/train-*
- config_name: 2012.main.ES
data_files:
- split: train
path: 2012.main.ES/train-*
- config_name: 2012.main.IT
data_files:
- split: train
path: 2012.main.IT/train-*
- config_name: 2012.main.RO
data_files:
- split: train
path: 2012.main.RO/train-*
- config_name: 2013.main.AR
data_files:
- split: train
path: 2013.main.AR/train-*
- config_name: 2013.main.BG
data_files:
- split: train
path: 2013.main.BG/train-*
- config_name: 2013.main.EN
data_files:
- split: train
path: 2013.main.EN/train-*
- config_name: 2013.main.ES
data_files:
- split: train
path: 2013.main.ES/train-*
- config_name: 2013.main.RO
data_files:
- split: train
path: 2013.main.RO/train-*
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: 5.49 MB
- Size of the generated dataset: 48.35 MB
- Total amount of disk used: 53.84 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: 0.22 MB
- Size of the generated dataset: 1.75 MB
- Total amount of disk used: 1.97 MB
An example of 'train' looks as follows.
2011.main.EN
- Size of downloaded dataset files: 0.20 MB
- Size of the generated dataset: 1.57 MB
- Total amount of disk used: 1.77 MB
An example of 'train' looks as follows.
2011.main.ES
- Size of downloaded dataset files: 0.22 MB
- Size of the generated dataset: 1.70 MB
- Total amount of disk used: 1.91 MB
An example of 'train' looks as follows.
2011.main.IT
- 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.RO
- Size of downloaded dataset files: 0.22 MB
- Size of the generated dataset: 1.74 MB
- Total amount of disk used: 1.96 MB
An example of 'train' looks as follows.
Data Fields
The data fields are the same among all splits.
2011.main.DE
topic_id
: astring
feature.topic_name
: astring
feature.test_id
: astring
feature.document_id
: astring
feature.document_str
: astring
feature.question_id
: astring
feature.question_str
: astring
feature.answer_options
: a dictionary feature containing:answer_id
: astring
feature.answer_str
: astring
feature.
correct_answer_id
: astring
feature.correct_answer_str
: astring
feature.
2011.main.EN
topic_id
: astring
feature.topic_name
: astring
feature.test_id
: astring
feature.document_id
: astring
feature.document_str
: astring
feature.question_id
: astring
feature.question_str
: astring
feature.answer_options
: a dictionary feature containing:answer_id
: astring
feature.answer_str
: astring
feature.
correct_answer_id
: astring
feature.correct_answer_str
: astring
feature.
2011.main.ES
topic_id
: astring
feature.topic_name
: astring
feature.test_id
: astring
feature.document_id
: astring
feature.document_str
: astring
feature.question_id
: astring
feature.question_str
: astring
feature.answer_options
: a dictionary feature containing:answer_id
: astring
feature.answer_str
: astring
feature.
correct_answer_id
: astring
feature.correct_answer_str
: astring
feature.
2011.main.IT
topic_id
: astring
feature.topic_name
: astring
feature.test_id
: astring
feature.document_id
: astring
feature.document_str
: astring
feature.question_id
: astring
feature.question_str
: astring
feature.answer_options
: a dictionary feature containing:answer_id
: astring
feature.answer_str
: astring
feature.
correct_answer_id
: astring
feature.correct_answer_str
: astring
feature.
2011.main.RO
topic_id
: astring
feature.topic_name
: astring
feature.test_id
: astring
feature.document_id
: astring
feature.document_str
: astring
feature.question_id
: astring
feature.question_str
: astring
feature.answer_options
: a dictionary feature containing:answer_id
: astring
feature.answer_str
: astring
feature.
correct_answer_id
: astring
feature.correct_answer_str
: astring
feature.
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.