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import os |
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import re |
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import xml.etree.ElementTree as ET |
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import datasets |
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XML_NAMESPACE = "{http://www.w3.org/XML/1998/namespace}" |
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DEFAULT_LANG = "default" |
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_CITATION = """\ |
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@misc{janes_preklop, |
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title = {Tweet code-switching corpus Janes-Preklop 1.0}, |
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author = {Reher, {\v S}pela and Erjavec, Toma{\v z} and Fi{\v s}er, Darja}, |
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url = {http://hdl.handle.net/11356/1154}, |
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note = {Slovenian language resource repository {CLARIN}.{SI}}, |
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copyright = {Creative Commons - Attribution-{ShareAlike} 4.0 International ({CC} {BY}-{SA} 4.0)}, |
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issn = {2820-4042}, |
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year = {2017} |
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} |
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""" |
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_DESCRIPTION = """\ |
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Janes-Preklop is a corpus of Slovene tweets that is manually annotated for code-switching (the use of words from two |
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or more languages within one sentence or utterance), according to the supplied typology. |
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""" |
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_HOMEPAGE = "http://nl.ijs.si/janes/" |
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_LICENSE = "Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)" |
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_URLS = { |
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"janes_preklop_tei": "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1154/Janes-Preklop.TEI.zip" |
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} |
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def namespace(element): |
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m = re.match(r'\{.*\}', element.tag) |
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return m.group(0) if m else '' |
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def word_info(wordlike_tag, _namespace): |
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if wordlike_tag.tag == f"{_namespace}c": |
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return None, None |
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elif wordlike_tag.tag in {f"{_namespace}w", f"{_namespace}pc"}: |
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_word = wordlike_tag.text.strip() |
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return [_word], None |
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words, lang = [], [] |
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if wordlike_tag.tag == f"{_namespace}choice": |
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reg_tag = wordlike_tag.find(f"{_namespace}reg") |
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for _child in reg_tag: |
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_child_words, _child_langs = word_info(_child, _namespace) |
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if _child_words is None: |
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continue |
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words.extend(_child_words) |
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if _child_langs is None: |
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_child_langs = [DEFAULT_LANG for _ in range(len(_child_words))] |
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lang.extend(_child_langs) |
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return words, lang |
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elif wordlike_tag.tag == f"{_namespace}seg": |
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codeswitch_lang = wordlike_tag.attrib.get(f"{XML_NAMESPACE}lang", DEFAULT_LANG) |
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_seg_words, _seg_langs = [], [] |
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for _child in wordlike_tag: |
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_child_words, _child_langs = word_info(_child, _namespace) |
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if _child_words is None: |
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continue |
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_seg_words.extend(_child_words) |
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if _child_langs is None: |
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_child_langs = [codeswitch_lang for _ in range(len(_child_words))] |
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_seg_langs.extend(_child_langs) |
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if codeswitch_lang != DEFAULT_LANG: |
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_seg_langs[0] = f"B-{_seg_langs[0]}" |
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for _i in range(1, len(_seg_words)): |
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_seg_langs[_i] = f"I-{_seg_langs[_i]}" |
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words.extend(_seg_words) |
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lang.extend(_seg_langs) |
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return words, lang |
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class JanesPreklop(datasets.GeneratorBasedBuilder): |
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"""Code-switched Slovene tweet dataset. """ |
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VERSION = datasets.Version("1.0.0") |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"words": datasets.Sequence(datasets.Value("string")), |
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"language": datasets.Sequence(datasets.Value("string")) |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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urls = _URLS["janes_preklop_tei"] |
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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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gen_kwargs={"file_path": os.path.join(data_dir, "Janes-Preklop.TEI", "janes.preklop.body.xml")}, |
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) |
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] |
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def _generate_examples(self, file_path): |
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curr_doc = ET.parse(file_path) |
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root = curr_doc.getroot() |
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NAMESPACE = namespace(root) |
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idx_ex = 0 |
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for curr_ex in root.iterfind(f"{NAMESPACE}ab"): |
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ex_words, ex_langs = [], [] |
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for child_tag in curr_ex: |
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if child_tag.tag not in {f"{NAMESPACE}s", f"{NAMESPACE}c"}: |
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continue |
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if child_tag.tag == f"{NAMESPACE}c": |
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continue |
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for word_or_seg_tag in child_tag: |
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_words, _langs = word_info(word_or_seg_tag, NAMESPACE) |
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if _words is None: |
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continue |
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if _langs is None: |
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_langs = [DEFAULT_LANG for _ in range(len(_words))] |
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ex_words.extend(_words) |
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ex_langs.extend(_langs) |
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yield idx_ex, { |
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"id": curr_ex.attrib[f"{XML_NAMESPACE}id"], |
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"words": ex_words, |
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"language": ex_langs |
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} |
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idx_ex += 1 |
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