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- ---
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- pretty_name: Opus100
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- task_categories:
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- - translation
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- multilinguality:
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- - translation
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- task_ids: []
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- download_size: 2556791
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- dataset_size: 713412
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- features:
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- - fr
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2270
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- num_examples: 2000
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- download_size: 2556791
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- dataset_size: 458746
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- - config_name: de-nl
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- features:
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- - de
2281
- - nl
2282
- splits:
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- - name: test
2284
- num_bytes: 403886
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- num_examples: 2000
2286
- download_size: 2556791
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- dataset_size: 403886
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- - name: translation
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- - ru
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- splits:
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- - name: test
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- num_bytes: 315779
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- num_examples: 2000
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- download_size: 2556791
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- dataset_size: 315779
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- - zh
2310
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- - name: test
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- num_bytes: 280397
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- download_size: 2556791
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- dataset_size: 280397
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- - config_name: fr-nl
2317
- features:
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- - name: translation
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- dtype:
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- splits:
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- num_bytes: 368646
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- num_examples: 2000
2328
- download_size: 2556791
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- dataset_size: 368646
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2331
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- num_examples: 2000
2342
- download_size: 2556791
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- dataset_size: 732724
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- - fr
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2354
- num_bytes: 619394
2355
- num_examples: 2000
2356
- download_size: 2556791
2357
- dataset_size: 619394
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2375
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2379
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2381
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2383
- num_examples: 2000
2384
- download_size: 2556791
2385
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2386
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2387
- features:
2388
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2389
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- - ru
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- - zh
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2396
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2397
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2398
- download_size: 2556791
2399
- dataset_size: 916114
2400
- ---
2401
-
2402
- # Dataset Card for Opus100
2403
-
2404
- ## Table of Contents
2405
- - [Dataset Description](#dataset-description)
2406
- - [Dataset Summary](#dataset-summary)
2407
- - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
2408
- - [Languages](#languages)
2409
- - [Dataset Structure](#dataset-structure)
2410
- - [Data Instances](#data-instances)
2411
- - [Data Fields](#data-fields)
2412
- - [Data Splits](#data-splits)
2413
- - [Dataset Creation](#dataset-creation)
2414
- - [Curation Rationale](#curation-rationale)
2415
- - [Source Data](#source-data)
2416
- - [Annotations](#annotations)
2417
- - [Personal and Sensitive Information](#personal-and-sensitive-information)
2418
- - [Considerations for Using the Data](#considerations-for-using-the-data)
2419
- - [Social Impact of Dataset](#social-impact-of-dataset)
2420
- - [Discussion of Biases](#discussion-of-biases)
2421
- - [Other Known Limitations](#other-known-limitations)
2422
- - [Additional Information](#additional-information)
2423
- - [Dataset Curators](#dataset-curators)
2424
- - [Licensing Information](#licensing-information)
2425
- - [Citation Information](#citation-information)
2426
- - [Contributions](#contributions)
2427
-
2428
- ## Dataset Description
2429
-
2430
- - **Homepage:** [Link](http://opus.nlpl.eu/opus-100.php)
2431
- - **Repository:** [GitHub](https://github.com/EdinburghNLP/opus-100-corpus)
2432
- - **Paper:** [ARXIV](https://arxiv.org/abs/2004.11867)
2433
- - **Leaderboard:**
2434
- - **Point of Contact:**
2435
-
2436
- ### Dataset Summary
2437
-
2438
- OPUS-100 is English-centric, meaning that all training pairs include English on either the source or target side. The corpus covers 100 languages (including English). Selected the languages based on the volume of parallel data available in OPUS.
2439
-
2440
- ### Supported Tasks and Leaderboards
2441
-
2442
- [More Information Needed]
2443
-
2444
- ### Languages
2445
-
2446
- OPUS-100 contains approximately 55M sentence pairs. Of the 99 language pairs, 44 have 1M sentence pairs of training data, 73 have at least 100k, and 95 have at least 10k.
2447
-
2448
- ## Dataset Structure
2449
-
2450
- ### Data Instances
2451
-
2452
- ```
2453
- {
2454
- "ca": "El departament de bombers té el seu propi equip d'investigació.",
2455
- "en": "Well, the fire department has its own investigative unit."
2456
- }
2457
- ```
2458
-
2459
- ### Data Fields
2460
-
2461
- - `src_tag`: `string` text in source language
2462
- - `tgt_tag`: `string` translation of source language in target language
2463
-
2464
- ### Data Splits
2465
-
2466
- The dataset is split into training, development, and test portions. Data was prepared by randomly sampled up to 1M sentence pairs per language pair for training and up to 2000 each for development and test. To ensure that there was no overlap (at the monolingual sentence level) between the training and development/test data, they applied a filter during sampling to exclude sentences that had already been sampled. Note that this was done cross-lingually so that, for instance, an English sentence in the Portuguese-English portion of the training data could not occur in the Hindi-English test set.
2467
-
2468
- ## Dataset Creation
2469
-
2470
- ### Curation Rationale
2471
-
2472
- [More Information Needed]
2473
-
2474
- ### Source Data
2475
-
2476
- [More Information Needed]
2477
-
2478
- #### Initial Data Collection and Normalization
2479
-
2480
- [More Information Needed]
2481
-
2482
- #### Who are the source language producers?
2483
-
2484
- [More Information Needed]
2485
-
2486
- ### Annotations
2487
-
2488
- #### Annotation process
2489
-
2490
- [More Information Needed]
2491
-
2492
- #### Who are the annotators?
2493
-
2494
- [More Information Needed]
2495
-
2496
- ### Personal and Sensitive Information
2497
-
2498
- [More Information Needed]
2499
-
2500
- ## Considerations for Using the Data
2501
-
2502
- ### Social Impact of Dataset
2503
-
2504
- [More Information Needed]
2505
-
2506
- ### Discussion of Biases
2507
-
2508
- [More Information Needed]
2509
-
2510
- ### Other Known Limitations
2511
-
2512
- [More Information Needed]
2513
-
2514
- ## Additional Information
2515
-
2516
- ### Dataset Curators
2517
-
2518
- [More Information Needed]
2519
-
2520
- ### Licensing Information
2521
-
2522
- [More Information Needed]
2523
-
2524
- ### Citation Information
2525
-
2526
- ```
2527
- @misc{zhang2020improving,
2528
- title={Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation},
2529
- author={Biao Zhang and Philip Williams and Ivan Titov and Rico Sennrich},
2530
- year={2020},
2531
- eprint={2004.11867},
2532
- archivePrefix={arXiv},
2533
- primaryClass={cs.CL}
2534
- }
2535
- ```
2536
-
2537
- ### Contributions
2538
-
2539
- Thanks to [@vasudevgupta7](https://github.com/vasudevgupta7) for adding this dataset.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 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opus100.py DELETED
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- # coding=utf-8
2
- # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
3
- #
4
- # Licensed under the Apache License, Version 2.0 (the "License");
5
- # you may not use this file except in compliance with the License.
6
- # You may obtain a copy of the License at
7
- #
8
- # http://www.apache.org/licenses/LICENSE-2.0
9
- #
10
- # Unless required by applicable law or agreed to in writing, software
11
- # distributed under the License is distributed on an "AS IS" BASIS,
12
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
- # See the License for the specific language governing permissions and
14
- # limitations under the License.
15
- """OPUS-100"""
16
-
17
-
18
- import datasets
19
-
20
-
21
- _CITATION = """\
22
- @misc{zhang2020improving,
23
- title={Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation},
24
- author={Biao Zhang and Philip Williams and Ivan Titov and Rico Sennrich},
25
- year={2020},
26
- eprint={2004.11867},
27
- archivePrefix={arXiv},
28
- primaryClass={cs.CL}
29
- }
30
- """
31
-
32
- _DESCRIPTION = """\
33
- OPUS-100 is English-centric, meaning that all training pairs include English on either the source or target side.
34
- The corpus covers 100 languages (including English).OPUS-100 contains approximately 55M sentence pairs.
35
- Of the 99 language pairs, 44 have 1M sentence pairs of training data, 73 have at least 100k, and 95 have at least 10k.
36
- """
37
-
38
- _URL = {
39
- "supervised": "https://object.pouta.csc.fi/OPUS-100/v1.0/opus-100-corpus-{}-v1.0.tar.gz",
40
- "zero-shot": "https://object.pouta.csc.fi/OPUS-100/v1.0/opus-100-corpus-zeroshot-v1.0.tar.gz",
41
- }
42
-
43
- _SupervisedLanguagePairs = [
44
- "af-en",
45
- "am-en",
46
- "an-en",
47
- "ar-en",
48
- "as-en",
49
- "az-en",
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- "be-en",
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- "br-en",
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- "cs-en",
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- "cy-en",
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- "en-eo",
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67
- "en-fi",
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71
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- "en-ja",
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86
- "en-kk",
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- "en-km",
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- "en-kn",
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- "en-ku",
91
- "en-ky",
92
- "en-li",
93
- "en-lt",
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- "en-lv",
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- "en-mg",
96
- "en-mk",
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- "en-ml",
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- "en-mn",
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- "en-mr",
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- "en-ms",
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- "en-mt",
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- "en-my",
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- "en-nb",
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- "en-ne",
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- "en-nl",
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- "en-nn",
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- "en-no",
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- "en-oc",
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- "en-or",
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- "en-pa",
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- "en-pl",
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- "en-ps",
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- "en-pt",
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- "en-ro",
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- "en-ru",
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- "en-rw",
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- "en-se",
118
- "en-sh",
119
- "en-si",
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- "en-sk",
121
- "en-sl",
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- "en-sq",
123
- "en-sr",
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- "en-sv",
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- "en-ta",
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- "en-te",
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- "en-tg",
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- "en-th",
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- "en-tk",
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- "en-tr",
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- "en-tt",
132
- "en-ug",
133
- "en-uk",
134
- "en-ur",
135
- "en-uz",
136
- "en-vi",
137
- "en-wa",
138
- "en-xh",
139
- "en-yi",
140
- "en-yo",
141
- "en-zh",
142
- "en-zu",
143
- ]
144
-
145
- _0shotLanguagePairs = [
146
- "ar-de",
147
- "ar-fr",
148
- "ar-nl",
149
- "ar-ru",
150
- "ar-zh",
151
- "de-fr",
152
- "de-nl",
153
- "de-ru",
154
- "de-zh",
155
- "fr-nl",
156
- "fr-ru",
157
- "fr-zh",
158
- "nl-ru",
159
- "nl-zh",
160
- "ru-zh",
161
- ]
162
-
163
-
164
- class Opus100Config(datasets.BuilderConfig):
165
- """BuilderConfig for Opus100"""
166
-
167
- def __init__(self, language_pair, **kwargs):
168
- super().__init__(**kwargs)
169
- """
170
-
171
- Args:
172
- language_pair: language pair, you want to load
173
- **kwargs: keyword arguments forwarded to super.
174
- """
175
- self.language_pair = language_pair
176
-
177
-
178
- class Opus100(datasets.GeneratorBasedBuilder):
179
- """OPUS-100 is English-centric, meaning that all training pairs include English on either the source or target side."""
180
-
181
- VERSION = datasets.Version("1.0.0")
182
-
183
- BUILDER_CONFIG_CLASS = Opus100Config
184
- BUILDER_CONFIGS = [
185
- Opus100Config(name=pair, description=_DESCRIPTION, language_pair=pair)
186
- for pair in _SupervisedLanguagePairs + _0shotLanguagePairs
187
- ]
188
-
189
- def _info(self):
190
- src_tag, tgt_tag = self.config.language_pair.split("-")
191
- return datasets.DatasetInfo(
192
- description=_DESCRIPTION,
193
- features=datasets.Features({"translation": datasets.features.Translation(languages=(src_tag, tgt_tag))}),
194
- supervised_keys=(src_tag, tgt_tag),
195
- homepage="http://opus.nlpl.eu/opus-100.php",
196
- citation=_CITATION,
197
- )
198
-
199
- def _split_generators(self, dl_manager):
200
-
201
- lang_pair = self.config.language_pair
202
- src_tag, tgt_tag = lang_pair.split("-")
203
-
204
- domain = "supervised"
205
- if lang_pair in _0shotLanguagePairs:
206
- domain = "zero-shot"
207
-
208
- if domain == "supervised":
209
- archive = dl_manager.download(_URL["supervised"].format(lang_pair))
210
- elif domain == "zero-shot":
211
- archive = dl_manager.download(_URL["zero-shot"])
212
-
213
- data_dir = "/".join(["opus-100-corpus", "v1.0", domain, lang_pair])
214
- output = []
215
-
216
- test = datasets.SplitGenerator(
217
- name=datasets.Split.TEST,
218
- # These kwargs will be passed to _generate_examples
219
- gen_kwargs={
220
- "filepath": f"{data_dir}/opus.{lang_pair}-test.{src_tag}",
221
- "labelpath": f"{data_dir}/opus.{lang_pair}-test.{tgt_tag}",
222
- "files": dl_manager.iter_archive(archive),
223
- },
224
- )
225
-
226
- available_files = [path for path, _ in dl_manager.iter_archive(archive)]
227
- if f"{data_dir}/opus.{lang_pair}-test.{src_tag}" in available_files:
228
- output.append(test)
229
-
230
- if domain == "supervised":
231
-
232
- train = datasets.SplitGenerator(
233
- name=datasets.Split.TRAIN,
234
- gen_kwargs={
235
- "filepath": f"{data_dir}/opus.{lang_pair}-train.{src_tag}",
236
- "labelpath": f"{data_dir}/opus.{lang_pair}-train.{tgt_tag}",
237
- "files": dl_manager.iter_archive(archive),
238
- },
239
- )
240
-
241
- if f"{data_dir}/opus.{lang_pair}-train.{src_tag}" in available_files:
242
- output.append(train)
243
-
244
- valid = datasets.SplitGenerator(
245
- name=datasets.Split.VALIDATION,
246
- # These kwargs will be passed to _generate_examples
247
- gen_kwargs={
248
- "filepath": f"{data_dir}/opus.{lang_pair}-dev.{src_tag}",
249
- "labelpath": f"{data_dir}/opus.{lang_pair}-dev.{tgt_tag}",
250
- "files": dl_manager.iter_archive(archive),
251
- },
252
- )
253
-
254
- if f"{data_dir}/opus.{lang_pair}-dev.{src_tag}" in available_files:
255
- output.append(valid)
256
-
257
- return output
258
-
259
- def _generate_examples(self, filepath, labelpath, files):
260
- """Yields examples."""
261
- src_tag, tgt_tag = self.config.language_pair.split("-")
262
- src, tgt = None, None
263
- for path, f in files:
264
- if path == filepath:
265
- src = f.read().decode("utf-8").split("\n")[:-1]
266
- elif path == labelpath:
267
- tgt = f.read().decode("utf-8").split("\n")[:-1]
268
- if src is not None and tgt is not None:
269
- for idx, (s, t) in enumerate(zip(src, tgt)):
270
- yield idx, {"translation": {src_tag: s, tgt_tag: t}}
271
- break