metadata

language:
  - en
  - multilingual
  - ar
  - bg
  - cs
  - da
  - de
  - el
  - es
  - et
  - fa
  - fi
  - fr
  - gu
  - he
  - hi
  - hr
  - hu
  - hy
  - id
  - it
  - ja
  - ka
  - ko
  - lt
  - lv
  - mk
  - mn
  - mr
  - my
  - nl
  - pl
  - pt
  - ro
  - ru
  - sk
  - sl
  - sq
  - sv
  - th
  - tr
  - uk
  - ur
  - vi
size_categories:
  - 10M<n<100M
task_categories:
  - feature-extraction
  - sentence-similarity
pretty_name: JW300
tags:
  - sentence-transformers
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configs:
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  - config_name: en-it
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        path: en-my/train-*
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        path: en-pl/train-*
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        path: en-ru/train-*
  - config_name: en-sk
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        path: en-sk/train-*
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        path: en-sl/train-*
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    data_files:
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        path: en-sq/train-*
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    data_files:
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        path: en-sv/train-*
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    data_files:
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        path: en-th/train-*
  - config_name: en-tr
    data_files:
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        path: en-tr/train-*
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    data_files:
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        path: en-uk/train-*
  - config_name: en-ur
    data_files:
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        path: en-ur/train-*
  - config_name: en-vi
    data_files:
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        path: en-vi/train-*

Dataset Card for Parallel Sentences - JW300

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. In particular, this dataset contains the JW300 dataset.

Related Datasets

The following datasets are also a part of the Parallel Sentences collection:

These datasets can be used to train multilingual sentence embedding models. For more information, see sbert.net - Multilingual Models.

Dataset Subsets

`all` subset

Columns: "english", "non_english"
Column types: str, str

Examples:

{
  "english": "It will really help me. I am a compulsive TV watcher.",
  "non_english": "سيكون هذا الفصل خير مساعد لي .‏"
}

Collection strategy: Combining all other subsets from this dataset.
Deduplified: No

`en-...` subsets

Columns: "english", "non_english"
Column types: str, str