|
--- |
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annotations_creators: |
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- no-annotation |
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language_creators: |
|
- found |
|
language: |
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- bs |
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- bg |
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- en |
|
- is |
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- hr |
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- cnr |
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- mk |
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- mt |
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- sl |
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- sr |
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- sq |
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- tr |
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license: |
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- cc0-1.0 |
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multilinguality: |
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- translation |
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pretty_name: MaCoCu_parallel |
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size_categories: |
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- 10M<n<100M |
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source_datasets: |
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- original |
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task_categories: |
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- translation |
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task_ids: [] |
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dataset_info: |
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- config_name: enis |
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features: |
|
- name: translation |
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dtype: |
|
translation: |
|
languages: |
|
- is |
|
- en |
|
splits: |
|
- name: train |
|
num_bytes: 133883139 |
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num_examples: 546172 |
|
download_size: 133883139 |
|
dataset_size: 133883139 |
|
- config_name: enbg |
|
features: |
|
- name: translation |
|
dtype: |
|
translation: |
|
languages: |
|
- bg |
|
- en |
|
splits: |
|
- name: train |
|
num_bytes: 133883139 |
|
num_examples: 546172 |
|
download_size: 133883139 |
|
dataset_size: 133883139 |
|
--- |
|
license: cc0-1.0 |
|
--- |
|
### Dataset Summary |
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The collection of MaCoCu parallel corpora have been crawled and consist of pairs of source and target segments (one or several sentences) and additional metadata. The following metadata is included: |
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- "src_url" and "trg_url": source and target document URL; |
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- "src_text" and "trg_text": text in non-English language and in English Language; |
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- "bleualign_score": similarity score as provided by the sentence alignment tool Bleualign (value between 0 and 1); |
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- "src_deferred_hash" and "trg_deferred_hash": hash identifier for the corresponding segment; |
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- "src_paragraph_id" and "trg_paragraph_id": identifier of the paragraph where the segment appears in the original document; |
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- "src_doc_title" and "trg_doc_title": title of the documents from which segments where obtained; |
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- "src_crawl_date" and "trg_crawl_date": date and time when source and target documents where donwoaded; |
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- "src_file_type" and "trg_file_type": type of the original documents (usually HTML format); |
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- "src_boilerplate" and "trg_boilerplate": are source or target segments boilerplates? |
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- "bifixer_hash": hash identifier for the segment pair; |
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- "bifixer_score": score that indicates how likely are segments to be correct in their corresponding language; |
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- "bicleaner_ai_score": score that indicates how likely are segments to be parallel; |
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- "biroamer_entities_detected": do any of the segments contain personal information? |
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- "dsi": a DSI class (“dsi”): information whether the segment is connected to any of Digital Service Infrastructure (DSI) classes (e.g., cybersecurity, e-health, e-justice, open-data-portal), defined by the Connecting Europe Facility (https://github.com/RikVN/DSI); |
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- "translation_direction": translation direction and machine translation identification ("translation-direction"): the source segment in each segment pair was identified by using a probabilistic model (https://github.com/RikVN/TranslationDirection), which also determines if the translation has been produced by a machine-translation system; |
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- "en_document_level_variant": the language variant of English (British or American, using a lexicon-based English variety classifier - https://pypi.org/project/abclf/) was identified on document and domain level; |
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- "domain_en": name of the web domain for the English document; |
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- "en_domain_level_variant": language variant for English at the level of the web domain. |
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|
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To load a language pair just indicate the dataset and the pair of languages with English first |
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|
|
```python |
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dataset = load_dataset("MaCoCu/parallel_data", "en-is") |
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``` |
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|
