metadata

language:
  - en
  - multilingual
  - ar
  - cs
  - de
  - es
  - fr
  - it
  - ja
  - nl
  - pt
  - ru
size_categories:
  - 100K<n<1M
task_categories:
  - feature-extraction
  - sentence-similarity
pretty_name: News-Commentary
tags:
  - sentence-transformers
dataset_info:
  - config_name: all
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
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        num_examples: 972552
    download_size: 212877098
    dataset_size: 364506039
  - config_name: en-ar
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
        num_bytes: 92586042
        num_examples: 160944
    download_size: 49722288
    dataset_size: 92586042
  - config_name: en-cs
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
        num_bytes: 49880143
        num_examples: 170683
    download_size: 32540459
    dataset_size: 49880143
  - config_name: en-de
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
        num_bytes: 67264401
        num_examples: 214971
    download_size: 41648198
    dataset_size: 67264401
  - config_name: en-es
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
        num_bytes: 10885552
        num_examples: 34352
    download_size: 6671353
    dataset_size: 10885552
  - config_name: en-fr
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
        num_bytes: 34229410
        num_examples: 106040
    download_size: 20771370
    dataset_size: 34229410
  - config_name: en-it
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
        num_bytes: 14672830
        num_examples: 45791
    download_size: 8938106
    dataset_size: 14672830
  - config_name: en-ja
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
        num_bytes: 541819
        num_examples: 1253
    download_size: 327264
    dataset_size: 541819
  - config_name: en-nl
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
        num_bytes: 7209024
        num_examples: 22890
    download_size: 4399324
    dataset_size: 7209024
  - config_name: en-pt
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
        num_bytes: 9170349
        num_examples: 29077
    download_size: 5684510
    dataset_size: 9170349
  - config_name: en-ru
    features:
      - name: english
        dtype: string
      - name: non_english
        dtype: string
    splits:
      - name: train
        num_bytes: 77891207
        num_examples: 183413
    download_size: 42240433
    dataset_size: 77891207
configs:
  - config_name: all
    data_files:
      - split: train
        path: all/train-*
  - config_name: en-ar
    data_files:
      - split: train
        path: en-ar/train-*
  - config_name: en-cs
    data_files:
      - split: train
        path: en-cs/train-*
  - config_name: en-de
    data_files:
      - split: train
        path: en-de/train-*
  - config_name: en-es
    data_files:
      - split: train
        path: en-es/train-*
  - config_name: en-fr
    data_files:
      - split: train
        path: en-fr/train-*
  - config_name: en-it
    data_files:
      - split: train
        path: en-it/train-*
  - config_name: en-ja
    data_files:
      - split: train
        path: en-ja/train-*
  - config_name: en-nl
    data_files:
      - split: train
        path: en-nl/train-*
  - config_name: en-pt
    data_files:
      - split: train
        path: en-pt/train-*
  - config_name: en-ru
    data_files:
      - split: train
        path: en-ru/train-*

Dataset Card for Parallel Sentences - News Commentary

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 News-Commentary 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": "Pure interests – expressed through lobbying power – were undoubtedly important to several key deregulation measures in the US, whose political system and campaign-finance rules are peculiarly conducive to the power of specific lobbies.",
  "non_english": "Заинтересованные группы, действующие посредством лоббирования власти, явились важными действующими лицами при принятии нескольких ключевых мер по отмене регулирующих норм в США, чья политическая система и правила финансирования кампаний особенно поддаются власти отдельных лобби."
}

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

`en-...` subsets

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