Datasets:
Tasks:
Summarization
Languages:
English
Multilinguality:
monolingual
Size Categories:
n<1K
Language Creators:
found
Annotations Creators:
crowdsourced
Source Datasets:
original
License:
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Dataset Card for "opinosis"
Dataset Summary
The Opinosis Opinion Dataset consists of sentences extracted from reviews for 51 topics. Topics and opinions are obtained from Tripadvisor, Edmunds.com and Amazon.com.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
default
- Size of downloaded dataset files: 0.75 MB
- Size of the generated dataset: 0.74 MB
- Total amount of disk used: 1.50 MB
An example of 'train' looks as follows.
{
"review_sents": "This is a fake topic. \nThe topics have multiple sentence inputs. \n",
"summaries": ["This is a gold summary for topic 1. \nSentences in gold summaries are separated by newlines.", "This is another gold summary for topic 1. \nSentences in gold summaries are separated by newlines."]
}
Data Fields
The data fields are the same among all splits.
default
review_sents: astringfeature.summaries: alistofstringfeatures.
Data Splits
| name | train |
|---|---|
| default | 51 |
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
The license for this dataset is Apache License 2.0 and can be found here.
Citation Information
@inproceedings{ganesan2010opinosis,
title={Opinosis: a graph-based approach to abstractive summarization of highly redundant opinions},
author={Ganesan, Kavita and Zhai, ChengXiang and Han, Jiawei},
booktitle={Proceedings of the 23rd International Conference on Computational Linguistics},
pages={340--348},
year={2010},
organization={Association for Computational Linguistics}
}
Contributions
Thanks to @thomwolf, @patrickvonplaten for adding this dataset.
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