Datasets:
Tasks:
Sentence Similarity
Modalities:
Text
Formats:
json
Sub-tasks:
semantic-similarity-classification
Languages:
English
Size:
100K - 1M
License:
espejelomar
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Update README.md
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README.md
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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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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
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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
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[More Information Needed](https://github.com/google-research-datasets/sentence-compression)
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### Languages
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### Curation Rationale
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### Contributions
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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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