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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

More Information Needed

Languages

More Information Needed

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: a string feature.
  • summaries: a list of string features.

Data Splits

name train
default 51

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

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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