Datasets:

Helsinki-NLP
/

multiun

@@ -1,495 +0,0 @@
----
-annotations_creators:
-- found
-language_creators:
-- found
-language:
-- ar
-- de
-- en
-- es
-- fr
-- ru
-- zh
-license:
-- unknown
-multilinguality:
-- multilingual
-size_categories:
-- 100K<n<1M
-source_datasets:
-- original
-task_categories:
-- translation
-task_ids: []
-paperswithcode_id: multiun
-pretty_name: Multilingual Corpus from United Nation Documents
-configs:
-- ar-de
-- ar-en
-- ar-es
-- ar-fr
-- ar-ru
-- ar-zh
-- de-en
-- de-es
-- de-fr
-- de-ru
-- de-zh
-- en-es
-- en-fr
-- en-ru
-- en-zh
-- es-fr
-- es-ru
-- es-zh
-- fr-ru
-- fr-zh
-- ru-zh
-dataset_info:
-- config_name: ar-de
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - ar
-        - de
-  splits:
-  - name: train
-    num_bytes: 94466397
-    num_examples: 165090
-  download_size: 21869935
-  dataset_size: 94466397
-- config_name: ar-en
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - ar
-        - en
-  splits:
-  - name: train
-    num_bytes: 4189852369
-    num_examples: 9759125
-  download_size: 1036296368
-  dataset_size: 4189852369
-- config_name: ar-es
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - ar
-        - es
-  splits:
-  - name: train
-    num_bytes: 4509675284
-    num_examples: 10119379
-  download_size: 1101206667
-  dataset_size: 4509675284
-- config_name: ar-fr
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - ar
-        - fr
-  splits:
-  - name: train
-    num_bytes: 4516850009
-    num_examples: 9929567
-  download_size: 1109705925
-  dataset_size: 4516850009
-- config_name: ar-ru
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - ar
-        - ru
-  splits:
-  - name: train
-    num_bytes: 5932866867
-    num_examples: 10206243
-  download_size: 1261123878
-  dataset_size: 5932866867
-- config_name: ar-zh
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - ar
-        - zh
-  splits:
-  - name: train
-    num_bytes: 3781658413
-    num_examples: 9832293
-  download_size: 1009696775
-  dataset_size: 3781658413
-- config_name: de-en
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - de
-        - en
-  splits:
-  - name: train
-    num_bytes: 76684549
-    num_examples: 162981
-  download_size: 19468529
-  dataset_size: 76684549
-- config_name: de-es
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - de
-        - es
-  splits:
-  - name: train
-    num_bytes: 80936653
-    num_examples: 162078
-  download_size: 20266591
-  dataset_size: 80936653
-- config_name: de-fr
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - de
-        - fr
-  splits:
-  - name: train
-    num_bytes: 81888435
-    num_examples: 164025
-  download_size: 20692837
-  dataset_size: 81888435
-- config_name: de-ru
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - de
-        - ru
-  splits:
-  - name: train
-    num_bytes: 111517934
-    num_examples: 164792
-  download_size: 23507789
-  dataset_size: 111517934
-- config_name: de-zh
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - de
-        - zh
-  splits:
-  - name: train
-    num_bytes: 70534818
-    num_examples: 176933
-  download_size: 19927209
-  dataset_size: 70534818
-- config_name: en-es
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - en
-        - es
-  splits:
-  - name: train
-    num_bytes: 4128141663
-    num_examples: 11350967
-  download_size: 1123164180
-  dataset_size: 4128141663
-- config_name: en-fr
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - en
-        - fr
-  splits:
-  - name: train
-    num_bytes: 4678055160
-    num_examples: 13172019
-  download_size: 1355002731
-  dataset_size: 4678055160
-- config_name: en-ru
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - en
-        - ru
-  splits:
-  - name: train
-    num_bytes: 5632662839
-    num_examples: 11654416
-  download_size: 1285801078
-  dataset_size: 5632662839
-- config_name: en-zh
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - en
-        - zh
-  splits:
-  - name: train
-    num_bytes: 2960376046
-    num_examples: 9564315
-  download_size: 900076520
-  dataset_size: 2960376046
-- config_name: es-fr
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - es
-        - fr
-  splits:
-  - name: train
-    num_bytes: 4454712498
-    num_examples: 11441889
-  download_size: 1195733510
-  dataset_size: 4454712498
-- config_name: es-ru
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - es
-        - ru
-  splits:
-  - name: train
-    num_bytes: 5442655730
-    num_examples: 10605056
-  download_size: 1228045966
-  dataset_size: 5442655730
-- config_name: es-zh
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - es
-        - zh
-  splits:
-  - name: train
-    num_bytes: 3223871198
-    num_examples: 9847770
-  download_size: 953250084
-  dataset_size: 3223871198
-- config_name: fr-ru
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - fr
-        - ru
-  splits:
-  - name: train
-    num_bytes: 5979879089
-    num_examples: 11761738
-  download_size: 1364307157
-  dataset_size: 5979879089
-- config_name: fr-zh
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - fr
-        - zh
-  splits:
-  - name: train
-    num_bytes: 3241098333
-    num_examples: 9690914
-  download_size: 962824881
-  dataset_size: 3241098333
-- config_name: ru-zh
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - ru
-        - zh
-  splits:
-  - name: train
-    num_bytes: 4233875537
-    num_examples: 9557007
-  download_size: 1037881127
-  dataset_size: 4233875537
----
-# Dataset Card for [Dataset Name]
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-## Dataset Description
-- **Homepage:**[MultiUN](http://www.euromatrixplus.net/multi-unp)
-- **Repository:**
-- **Paper:**
-- **Leaderboard:**
-- **Point of Contact:**
-### Dataset Summary
-This is a collection of translated documents from the United Nations.
-This corpus is available in all 6 official languages of the UN
-consisting of around 300 million words per language
-### Supported Tasks and Leaderboards
-The underlying task is machine translation.
-### Languages
-[More Information Needed]
-## Dataset Structure
-### Data Instances
-[More Information Needed]
-### Data Fields
-[More Information Needed]
-### Data Splits
-[More Information Needed]
-## Dataset Creation
-### Curation Rationale
-[More Information Needed]
-### Source Data
-#### Initial Data Collection and Normalization
-[More Information Needed]
-#### Who are the source language producers?
-[More Information Needed]
-### Annotations
-#### Annotation process
-[More Information Needed]
-#### Who are the annotators?
-[More Information Needed]
-### Personal and Sensitive Information
-[More Information Needed]
-## Considerations for Using the Data
-### Social Impact of Dataset
-[More Information Needed]
-### Discussion of Biases
-[More Information Needed]
-### Other Known Limitations
-[More Information Needed]
-## Additional Information
-### Dataset Curators
-[More Information Needed]
-### Licensing Information
-[More Information Needed]
-### Citation Information
-```
-@inproceedings{eisele-chen-2010-multiun,
-    title = "{M}ulti{UN}: A Multilingual Corpus from United Nation Documents",
-    author = "Eisele, Andreas  and
-      Chen, Yu",
-    booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
-    month = may,
-    year = "2010",
-    address = "Valletta, Malta",
-    publisher = "European Language Resources Association (ELRA)",
-    url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/686_Paper.pdf",
-    abstract = "This paper describes the acquisition, preparation and properties of a corpus extracted from the official documents of the United Nations (UN). This corpus is available in all 6 official languages of the UN, consisting of around 300 million words per language. We describe the methods we used for crawling, document formatting, and sentence alignment. This corpus also includes a common test set for machine translation. We present the results of a French-Chinese machine translation experiment performed on this corpus.",
-}
-```
-```
-@InProceedings{TIEDEMANN12.463,
-  author = {J�rg Tiedemann},
-  title = {Parallel Data, Tools and Interfaces in OPUS},
-  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
-  year = {2012},
-  month = {may},
-  date = {23-25},
-  address = {Istanbul, Turkey},
-  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Ugur Dogan and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis},
-  publisher = {European Language Resources Association (ELRA)},
-  isbn = {978-2-9517408-7-7},
-}
-```
-### Contributions
-Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset.

dataset_infos.json DELETED Viewed

@@ -1 +0,0 @@

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This corpus also includes a common test set for machine translation. We present the results of a French-Chinese machine translation experiment performed on this corpus.\",\n}\n\nJ. Tiedemann, 2012, Parallel Data, Tools and Interfaces in OPUS. 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This corpus also includes a common test set for machine translation. We present the results of a French-Chinese machine translation experiment performed on this corpus.\",\n}\n\nJ. Tiedemann, 2012, Parallel Data, Tools and Interfaces in OPUS. 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un_multi.py DELETED Viewed

@@ -1,109 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""MultiUN: Multilingual UN Parallel Text 2000—2009"""
-import itertools
-import os
-import datasets
-_CITATION = """\
-@inproceedings{eisele-chen-2010-multiun,
-    title = "{M}ulti{UN}: A Multilingual Corpus from United Nation Documents",
-    author = "Eisele, Andreas  and
-      Chen, Yu",
-    booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
-    month = may,
-    year = "2010",
-    address = "Valletta, Malta",
-    publisher = "European Language Resources Association (ELRA)",
-    url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/686_Paper.pdf",
-    abstract = "This paper describes the acquisition, preparation and properties of a corpus extracted from the official documents of the United Nations (UN). This corpus is available in all 6 official languages of the UN, consisting of around 300 million words per language. We describe the methods we used for crawling, document formatting, and sentence alignment. This corpus also includes a common test set for machine translation. We present the results of a French-Chinese machine translation experiment performed on this corpus.",
-}
-@InProceedings{TIEDEMANN12.463,
-  author = {J�rg Tiedemann},
-  title = {Parallel Data, Tools and Interfaces in OPUS},
-  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
-  year = {2012},
-  month = {may},
-  date = {23-25},
-  address = {Istanbul, Turkey},
-  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Ugur Dogan and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis},
-  publisher = {European Language Resources Association (ELRA)},
-  isbn = {978-2-9517408-7-7},
-}
-"""
-_DESCRIPTION = """\
-This is a collection of translated documents from the United Nations. \
-This corpus is available in all 6 official languages of the UN, \
-consisting of around 300 million words per language
-"""
-_HOMEPAGE = "http://www.euromatrixplus.net/multi-un/"
-_LANGUAGES = ["ar", "de", "en", "es", "fr", "ru", "zh"]
-_LANGUAGE_PAIRS = list(itertools.combinations(_LANGUAGES, 2))
-_BASE_URL = "http://opus.nlpl.eu/download.php?f=MultiUN/v1/moses"
-_URLS = {f"{l1}-{l2}": f"{_BASE_URL}/{l1}-{l2}.txt.zip" for l1, l2 in _LANGUAGE_PAIRS}
-class UnMulti(datasets.GeneratorBasedBuilder):
-    """MultiUN: Multilingual UN Parallel Text 2000—2009"""
-    VERSION = datasets.Version("1.0.0")
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name=f"{l1}-{l2}", version=datasets.Version("1.0.0"), description=f"MultiUN {l1}-{l2}")
-        for l1, l2 in _LANGUAGE_PAIRS
-    ]
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {"translation": datasets.features.Translation(languages=tuple(self.config.name.split("-")))}
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        lang_pair = self.config.name.split("-")
-        data_dir = dl_manager.download_and_extract(_URLS[self.config.name])
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "source_file": os.path.join(data_dir, f"MultiUN.{self.config.name}.{lang_pair[0]}"),
-                    "target_file": os.path.join(data_dir, f"MultiUN.{self.config.name}.{lang_pair[1]}"),
-                },
-            ),
-        ]
-    def _generate_examples(self, source_file, target_file):
-        source, target = tuple(self.config.name.split("-"))
-        with open(source_file, encoding="utf-8") as src_f, open(target_file, encoding="utf-8") as tgt_f:
-            for idx, (l1, l2) in enumerate(zip(src_f, tgt_f)):
-                result = {"translation": {source: l1.strip(), target: l2.strip()}}
-                yield idx, result