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  - en
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  paperswithcode_id: embedding-data/sentence-compression
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  pretty_name: sentence-compression
 
 
 
 
 
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  ---
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  # Dataset Card for "sentence-compression"
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  - **Total amount of disk used:** 14.2 MB
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  ### Dataset Summary
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- Large corpus of uncompressed and compressed sentences from news articles.
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-
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  The dataset is provided "AS IS" without any warranty, express or implied.
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- Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.
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-
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- The algorithm to collect the data is described here: Overcoming the Lack of Parallel Data in Sentence Compression,
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- Katja Filippova and Yasemin Altun, Proceedings of the 2013 Conference on Empirical Methods in
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- Natural Language Processing (EMNLP '13), pp. 1481-1491. [pdf](https://aclanthology.org/D13-1155.pdf)
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  Disclaimer: The team releasing sentence-compression did not upload the dataset to the Hub and did not write a dataset card. These steps were done by the Hugging Face team.
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- ### Supported Tasks and Leaderboards
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-
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- [More Information Needed](https://github.com/google-research-datasets/sentence-compression)
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-
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  ### Languages
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-
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- [More Information Needed](https://github.com/google-research-datasets/sentence-compression)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Curation Rationale
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@@ -117,6 +142,6 @@ Disclaimer: The team releasing sentence-compression did not upload the dataset t
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  ### Contributions
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- Thanks to [@katja-f](https://github.com/katja-f), [Google Research Datasets](https://github.com/google-research-datasets), [@dave-orr](https://github.com/dave-orr) for adding this dataset.
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  - en
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  paperswithcode_id: embedding-data/sentence-compression
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  pretty_name: sentence-compression
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+ task_categories:
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+ - sentence-similarity
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+ - paraphrase-mining
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+ task_ids:
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+ - semantic-similarity-classification
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  ---
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  # Dataset Card for "sentence-compression"
 
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  - **Total amount of disk used:** 14.2 MB
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  ### Dataset Summary
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+ Dataset with pairs of equivalent sentences.
 
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  The dataset is provided "AS IS" without any warranty, express or implied.
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+ Google disclaims all liability for any damages, direct or indirect, resulting from using the dataset.
 
 
 
 
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  Disclaimer: The team releasing sentence-compression did not upload the dataset to the Hub and did not write a dataset card. These steps were done by the Hugging Face team.
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+ ### Supported Tasks
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+ - [Sentence Transformers](https://huggingface.co/sentence-transformers) training; useful for semantic search and sentence similarity.
 
 
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  ### Languages
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+ - English.
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+ ## Dataset Structure
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+ Each example in the dataset contains pairs of equivalent sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value".
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+ ```
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+ {"set": [sentence_1, sentence_2]}
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+ {"set": [sentence_1, sentence_2]}
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+ ...
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+ {"set": [sentence_1, sentence_2]}
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+ ```
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+ This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar pairs of sentences.
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+ ### Usage Example
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+ Install the 🤗 Datasets library with `pip install datasets` and load the dataset from the Hub with:
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+ ```python
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+ from datasets import load_dataset
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+ dataset = load_dataset("embedding-data/sentence-compression")
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+ ```
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+ The dataset is loaded as a `DatasetDict` and has the format:
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+ ```python
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+ DatasetDict({
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+ train: Dataset({
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+ features: ['set'],
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+ num_rows: 180000
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+ })
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+ })
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+ ```
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+ Review an example `i` with:
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+ ```python
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+ dataset["train"][i]["set"]
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+ ```
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  ### Curation Rationale
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  ### Contributions
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+
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