README.md

---
language:
- en
- multilingual
- bg
- cs
- da
- de
- el
- es
- et
- fi
- fr
- hu
- it
- lt
- lv
- nl
- pl
- pt
- ro
- sk
- sl
- sv
size_categories:
- 10M<n<100M
task_categories:
- feature-extraction
- sentence-similarity
pretty_name: Europarl
tags:
- sentence-transformers
dataset_info:
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configs:
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- config_name: en-bg
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- config_name: en-es
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- config_name: en-fr
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- config_name: en-hu
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- config_name: en-it
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    path: en-it/train-*
- config_name: en-lt
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    path: en-lt/train-*
- config_name: en-lv
  data_files:
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- config_name: en-nl
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- config_name: en-pl
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- config_name: en-pt
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    path: en-pt/train-*
- config_name: en-ro
  data_files:
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    path: en-ro/train-*
- config_name: en-sk
  data_files:
  - split: train
    path: en-sk/train-*
- config_name: en-sl
  data_files:
  - split: train
    path: en-sl/train-*
- config_name: en-sv
  data_files:
  - split: train
    path: en-sv/train-*
---

# Dataset Card for Parallel Sentences - Europarl

This dataset contains parallel sentences (i.e. English sentence + the same sentences in another language) for numerous other languages. Most of the sentences originate from the [OPUS website](https://opus.nlpl.eu/).
In particular, this dataset contains the [Europarl](https://opus.nlpl.eu/Europarl/corpus/version/Europarl) dataset.

## Related Datasets

The following datasets are also a part of the Parallel Sentences collection:
* [parallel-sentences-europarl](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-europarl)
* [parallel-sentences-global-voices](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-global-voices)
* [parallel-sentences-muse](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-muse)
* [parallel-sentences-jw300](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-jw300)
* [parallel-sentences-news-commentary](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-news-commentary)
* [parallel-sentences-opensubtitles](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-opensubtitles)
* [parallel-sentences-talks](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-talks)
* [parallel-sentences-tatoeba](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-tatoeba)
* [parallel-sentences-wikimatrix](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-wikimatrix)
* [parallel-sentences-wikititles](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-wikititles)
* [parallel-sentences-ccmatrix](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-ccmatrix)

These datasets can be used to train multilingual sentence embedding models. For more information, see [sbert.net - Multilingual Models](https://www.sbert.net/examples/training/multilingual/README.html).

## Dataset Subsets

### `all` subset

* Columns: "english", "non_english"
* Column types: `str`, `str`
* Examples:
    ```python
    {
      "english": "Membership of Parliament: see Minutes",
  	  "non_english": "Състав на Парламента: вж. протоколи"
    }
    ```
* Collection strategy: Combining all other subsets from this dataset.
* Deduplified: No

### `en-...` subsets

* Columns: "english", "non_english"
* Column types: `str`, `str`
* Examples:
    ```python
    {
      "english": "Resumption of the session",
      "non_english": "Reanudación del período de sesiones"
    }
    ```
* Collection strategy: Processing the raw data from [parallel-sentences](https://huggingface.co/datasets/sentence-transformers/parallel-sentences) and formatting it in Parquet, followed by deduplication.
* Deduplified: Yes