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README.md

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----
-annotations_creators:
-- expert-generated
-- found
-language:
-- en
-- sl
-language_creators:
-- crowdsourced
-license:
-- cc-by-sa-4.0
-multilinguality:
-- translation
-pretty_name: RSDO4 en-sl parallel corpus
-size_categories:
-- 100K<n<1M
-source_datasets: []
-tags:
-- parallel data
-- rsdo
-task_categories:
-- translation
-- text2text-generation
-- text-generation
-task_ids: []
----
-
-# Dataset Card for RSDO4 en-sl parallel corpus
-
-### Dataset Summary
-
-The RSDO4 parallel corpus of English-Slovene and Slovene-English translation pairs was collected as part of work package 4 of the Slovene in the Digital Environment project. It contains texts collected from public institutions and texts submitted by individual donors through the text collection portal created within the project. The corpus consists of 964433 translation pairs (extracted from standard translation formats (TMX, XLIFF) or manually aligned) in randomized order which can be used for machine translation training.
-
-### Supported Tasks and Leaderboards
-
-Machine translation. 
-
-### Languages
-
-English, Slovenian.
-
-## Dataset Structure
-
-### Data Instances
-
-A sample instance from the dataset:
-```
-{
-  'en_seq': 'the total value of its assets exceeds EUR 30000000000;', 
-  'sl_seq': 'skupna vrednost njenih sredstev presega 30000000000 EUR'
-}
-```
-
-### Data Fields
-
-- `en_seq`: a string containing the English sequence; 
-- `sl_seq`: a string containing the Slovene sequence.
-
-## Additional Information
-
-### Dataset Curators
-
-Andraž Repar and Iztok Lebar Bajec. 
-
-### Licensing Information
-
-CC BY-SA 4.0.
-
-### Citation Information
-
-```
-@misc{rsdo4_en_sl,
- title = {Parallel corpus {EN}-{SL} {RSDO4} 1.0},
- author = {Repar, Andra{\v z} and Lebar Bajec, Iztok},
- url = {http://hdl.handle.net/11356/1457},
- year = {2021}
-}
-```
-
-### Contributions
-
-Thanks to [@matejklemen](https://github.com/matejklemen) for adding this dataset.

default/rsdo4_en_sl-train.parquet

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rsdo4_en_sl.py

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-""" rsdo4_en_sl is a parallel corpus of English-Slovene and Slovene-English translation pairs."""
-import xml.etree.ElementTree as ET
-import os
-
-import datasets
-
-
-_CITATION = """\
-@misc{rsdo4_en_sl,
- title = {Parallel corpus {EN}-{SL} {RSDO4} 1.0},
- author = {Repar, Andra{\v z} and Lebar Bajec, Iztok},
- url = {http://hdl.handle.net/11356/1457},
- year = {2021}
-}
-"""
-
-_DESCRIPTION = """\
-The RSDO4 parallel corpus of English-Slovene and Slovene-English translation pairs was collected as part of work 
-package 4 of the Slovene in the Digital Environment project. It contains texts collected from public institutions 
-and texts submitted by individual donors through the text collection portal created within the project. The corpus 
-consists of 964433 translation pairs (extracted from standard translation formats (TMX, XLIFF) or manually aligned) 
-in randomized order which can be used for machine translation training.
-"""
-
-_HOMEPAGE = "http://hdl.handle.net/11356/1457"
-
-_LICENSE = "Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)"
-
-_URLS = {
-    "rsdo4_en_sl": "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1457/rsdo4-parallel-corpus-1-0.tmx.zip"
-}
-
-XML_NAMESPACE = "{http://www.w3.org/XML/1998/namespace}"
-
-
-class RSDO4EnSl(datasets.GeneratorBasedBuilder):
-    """rsdo4_en_sl is a parallel corpus of English-Slovene and Slovene-English translation pairs."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "en_seq": datasets.Value("string"),
-                "sl_seq": datasets.Value("string"),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        urls = _URLS["rsdo4_en_sl"]
-        data_dir = dl_manager.download_and_extract(urls)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "file_path": os.path.join(data_dir, "rsdo4-parallel-corpus-1-0.tmx")
-                }
-            )
-        ]
-
-    def _generate_examples(self, file_path):
-        doc = ET.parse(file_path)
-        root = doc.getroot()
-
-        for i, curr_unit in enumerate(root.iterfind(".//tu")):
-            translation_pair = curr_unit.findall("tuv")
-
-            formatted_pair = {}
-            for curr_seq in translation_pair:
-                # Not sure whether the languages are erroneously swapped or whether xml:lang represents the "language direction"
-                seq_lang = "sl" if curr_seq.attrib[f"{XML_NAMESPACE}lang"] == "en" else "en"
-
-                curr_text = curr_seq.find("seg").text
-                curr_text = "" if curr_text is None else curr_text.strip()
-                formatted_pair[f"{seq_lang}_seq"] = curr_text
-
-            yield i, formatted_pair