Datasets:

Task Categories: translation
Multilinguality: translation
Size Categories: 100K<n<1M
Language Creators: found
Annotations Creators: found
Source Datasets: original
Licenses: unknown
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Update files from the datasets library (from 1.2.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ annotations_creators:
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+ - found
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+ language_creators:
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+ - found
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+ languages:
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+ - en
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+ - fa
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+ licenses:
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+ - unknown
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+ multilinguality:
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+ - translation
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+ size_categories:
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+ - 1k<10K
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+ source_datasets:
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+ - original
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+ task_categories:
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+ - conditional-text-generation
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+ task_ids:
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+ - machine-translation
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+ ---
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+
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+ # Dataset Card for [tep_en_fa_para]
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+
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+ ## Table of Contents
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks](#supported-tasks-and-leaderboards)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-instances)
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+ - [Data Splits](#data-instances)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
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+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:**[TEP: Tehran English-Persian parallel corpus](http://opus.nlpl.eu/TEP.php)
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+ - **Repository:**
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+ - **Paper:**
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+ - **Leaderboard:**
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+ - **Point of Contact:**
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+
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+ ### Dataset Summary
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+
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+ TEP: Tehran English-Persian parallel corpus. The first free Eng-Per corpus, provided by the Natural Language and Text Processing Laboratory, University of Tehran.
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+
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+ ### Supported Tasks and Leaderboards
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+
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+ The underlying task is machine translation for language pair English-Persian
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+
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+ ### Languages
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+
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+ English, Persian
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ [More Information Needed]
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+
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+ ### Data Fields
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+
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+ [More Information Needed]
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+
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+ ### Data Splits
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+
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+ [More Information Needed]
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+
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+ ## Dataset Creation
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+
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+ ### Curation Rationale
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+
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+ [More Information Needed]
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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+ [More Information Needed]
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+
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+ #### Who are the source language producers?
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+
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+ [More Information Needed]
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+
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+ ### Annotations
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+
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+ #### Annotation process
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+
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+ [More Information Needed]
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+
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+ #### Who are the annotators?
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+
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+ [More Information Needed]
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+
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+ ### Personal and Sensitive Information
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+
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+ [More Information Needed]
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+
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+ ## Considerations for Using the Data
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+
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+ ### Social Impact of Dataset
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+
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+ [More Information Needed]
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+
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+ ### Discussion of Biases
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+
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+ [More Information Needed]
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+
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+ ### Other Known Limitations
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+
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+ [More Information Needed]
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+
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+ ## Additional Information
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+
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+ ### Dataset Curators
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+
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+ [More Information Needed]
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+
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+ ### Licensing Information
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+
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+ [More Information Needed]
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+
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+ ### Citation Information
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+ M. T. Pilevar, H. Faili, and A. H. Pilevar, “TEP: Tehran English-Persian Parallel Corpus”, in proceedings of 12th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2011).
dataset_infos.json ADDED
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+ {"en-fa": {"description": "TEP: Tehran English-Persian parallel corpus. The first free Eng-Per corpus, provided by the Natural Language and Text Processing Laboratory, University of Tehran.\n", "citation": "@InProceedings{\u201cTEP: Tehran English-Persian Parallel Corpus\u201d,\ntitle = {TEP: Tehran English-Persian Parallel Corpus\u201d, in proceedings of 12th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2011)},\nauthors={M. T. Pilevar, H. Faili, and A. H. Pilevar, },\nyear={2011}\n}\n", "homepage": "http://opus.nlpl.eu/TEP.php", "license": "", "features": {"translation": {"languages": ["en", "fa"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": null, "builder_name": "tep_en_fa_para", "config_name": "en-fa", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 58735557, "num_examples": 612087, "dataset_name": "tep_en_fa_para"}}, "download_checksums": {"https://object.pouta.csc.fi/OPUS-TEP/v1/moses/en-fa.txt.zip": {"num_bytes": 16353318, "checksum": "190690734392e1898aaee2e46093883c086de3e11e903ab3c07fac54e350a238"}}, "download_size": 16353318, "post_processing_size": null, "dataset_size": 58735557, "size_in_bytes": 75088875}}
dummy/en-fa/1.1.0/dummy_data.zip ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:ad9fa8ee734f22f609fda627b6bc5bd4b2c5d593736fb5c57d6ea22127fdbb7b
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+ size 792
tep_en_fa_para.py ADDED
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+ # coding=utf-8
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+ # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
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+ # You may obtain a copy of the License at
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+ #
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+ # http://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+ """TEP: Tehran English-Persian parallel corpus."""
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+
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+ from __future__ import absolute_import, division, print_function
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+
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+ import os
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+
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+ import datasets
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+
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+
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+ _CITATION = """\
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+ @InProceedings{“TEP: Tehran English-Persian Parallel Corpus”,
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+ title = {TEP: Tehran English-Persian Parallel Corpus”, in proceedings of 12th International Conference \
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+ on Intelligent Text Processing and Computational Linguistics (CICLing-2011)},
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+ authors={M. T. Pilevar, H. Faili, and A. H. Pilevar, },
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+ year={2011}
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+ }
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+ """
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+
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+
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+ _DESCRIPTION = """\
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+ TEP: Tehran English-Persian parallel corpus. The first free Eng-Per corpus, provided by the Natural Language and Text Processing Laboratory, University of Tehran.
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+ """
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+
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+
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+ _HOMEPAGE = "http://opus.nlpl.eu/TEP.php"
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+
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+
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+ _LICENSE = ""
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+
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+
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+ _URLs = {"train": "https://object.pouta.csc.fi/OPUS-TEP/v1/moses/en-fa.txt.zip"}
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+
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+
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+ class TepEnFaPara(datasets.GeneratorBasedBuilder):
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+ """TEP: Tehran English-Persian parallel corpus."""
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+
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+ VERSION = datasets.Version("1.1.0")
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+
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+ BUILDER_CONFIGS = [
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+ datasets.BuilderConfig(name="en-fa", version=VERSION),
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+ ]
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+
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+ def _info(self):
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=datasets.Features(
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+ {"translation": datasets.features.Translation(languages=tuple(self.config.name.split("-")))}
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+ ),
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+ supervised_keys=None,
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+ homepage="http://opus.nlpl.eu/TEP.php",
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ """Returns SplitGenerators."""
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+ data_dir = dl_manager.download_and_extract(_URLs)
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={
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+ "source_file": os.path.join(data_dir["train"], "TEP.en-fa.en"),
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+ "target_file": os.path.join(data_dir["train"], "TEP.en-fa.fa"),
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+ "split": "train",
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+ },
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+ ),
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+ ]
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+
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+ def _generate_examples(self, source_file, target_file, split):
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+ """This function returns the examples in the raw (text) form."""
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+ with open(source_file, encoding="utf-8") as f:
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+ source_sentences = f.read().split("\n")
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+ with open(target_file, encoding="utf-8") as f:
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+ target_sentences = f.read().split("\n")
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+
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+ assert len(target_sentences) == len(source_sentences), "Sizes do not match: %d vs %d for %s vs %s." % (
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+ len(source_sentences),
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+ len(target_sentences),
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+ source_file,
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+ target_file,
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+ )
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+
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+ source, target = tuple(self.config.name.split("-"))
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+ for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)):
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+ result = {"translation": {source: l1, target: l2}}
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+ yield idx, result