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  - en
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  paperswithcode_id: embedding-data/simple-wiki
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  pretty_name: simple-wiki
 
 
 
 
 
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  ---
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  # Dataset Card for "simple-wiki"
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  - **Point of Contact:** [David Kauchak](dkauchak@cs.pomona.edu)
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  ### Dataset Summary
 
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- ### Supported Tasks and Leaderboards
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-
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- [More Information Needed](https://cs.pomona.edu/~dkauchak/simplification/)
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-
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  ### Languages
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-
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- [More Information Needed](https://cs.pomona.edu/~dkauchak/simplification/)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Curation Rationale
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  [More Information Needed](https://cs.pomona.edu/~dkauchak/simplification/)
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  ### Contributions
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- Thanks to [William Coster](wpc02009@pomona.edu), [David Kauchak](dkauchak@cs.pomona.edu) for adding this dataset.
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  - en
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  paperswithcode_id: embedding-data/simple-wiki
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  pretty_name: simple-wiki
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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 "simple-wiki"
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  - **Point of Contact:** [David Kauchak](dkauchak@cs.pomona.edu)
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  ### Dataset Summary
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+ This dataset contains pairs of equivalent sentences obtained from Wikipedia.
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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 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/simple-wiki")
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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: 102225
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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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  [More Information Needed](https://cs.pomona.edu/~dkauchak/simplification/)
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  ### Contributions