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import os |
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from pathlib import Path |
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import datasets |
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from bs4 import BeautifulSoup |
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_CITATION = """\ |
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@article{ite2003corpas, |
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title={Corpas Náisiúnta na Gaeilge/National Corpus of Irish, Volume 1}, |
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author={Institiúid Teangeolaíochta Éireann}, |
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journal={Dublin: ITÉ}, |
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year={2003} |
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} |
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""" |
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_DESCRIPTION = """\ |
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Corpus of written Irish. |
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""" |
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_TEXTDIRS = [ |
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"fiction", "information", "instruction", "non_fiction", "official" |
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] |
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class CNGDataset(datasets.GeneratorBasedBuilder): |
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"""National Corpus of Irish.""" |
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VERSION = datasets.Version("1.1.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="documents", version=VERSION, description="Plain text portion of the corpus: whole documents"), |
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datasets.BuilderConfig(name="paragraphs", version=VERSION, description="Plain text portion of the corpus: paragraphs"), |
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datasets.BuilderConfig(name="pos", version=VERSION, description="Part-of-speech tagging subset"), |
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] |
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def _info(self): |
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if self.config.name == "documents" or self.config.name == "paragraphs": |
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features = datasets.Features( |
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{ |
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"title": datasets.Value("string"), |
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"doc_id": datasets.Value("string"), |
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"author": datasets.Value("string"), |
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"date": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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"classes": datasets.Sequence(datasets.Value("string")) |
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} |
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) |
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else: |
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features = datasets.Features( |
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{ |
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"title": datasets.Value("string"), |
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"doc_id": datasets.Value("string"), |
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"author": datasets.Value("string"), |
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"date": datasets.Value("string"), |
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"classes": datasets.Sequence(datasets.Value("string")), |
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"words": datasets.Sequence(datasets.Value("string")), |
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"pos": 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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supervised_keys=None, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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manual_dir = os.path.abspath(os.path.expanduser(dl_manager.manual_dir)) |
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if not os.path.exists(manual_dir): |
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raise FileNotFoundError( |
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"{} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('phonlab-tcd/cngv1', data_dir=...)` with the path to the corpus directory".format( |
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manual_dir |
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) |
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) |
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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={ |
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"data_dir": manual_dir, |
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"split": "train", |
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}, |
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), |
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] |
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def _generate_examples( |
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self, data_dir, split |
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): |
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""" Yields examples as (key, example) tuples. """ |
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if self.config.name == "documents" or self.config.name == "paragraphs": |
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dirs = _TEXTDIRS |
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else: |
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dirs = ["pos"] |
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cng_path = Path(data_dir) |
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_id = 1 |
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for dir in dirs: |
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dir_path = cng_path / dir |
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for filepath in dir_path.glob('*.SGM'): |
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with open(filepath, encoding="utf-16-le") as f: |
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fid = filepath.stem |
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content = f.read() |
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soup = BeautifulSoup(content, 'html.parser') |
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title = _get_title(soup) |
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author = _get_author(soup) |
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classes = _get_categories(content) |
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date = _get_creation(soup) |
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if self.config.name == "pos": |
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for sent in _get_pos(soup): |
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words = [tok["word"] for tok in sent] |
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tags = [tok["msd"] for tok in sent] |
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yield _id, { |
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"title": title, |
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"doc_id": fid, |
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"author": author, |
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"date": date, |
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"classes": classes, |
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"words": words, |
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"pos": tags |
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} |
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_id += 1 |
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else: |
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text = _get_paragraphs(soup) |
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if self.config.name == "documents": |
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text = ["\n".join(text)] |
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for para in text: |
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yield _id, { |
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"title": title, |
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"doc_id": fid, |
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"author": author, |
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"date": date, |
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"classes": classes, |
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"text": para |
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} |
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_id += 1 |
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def _get_title(soup): |
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title = soup.find("title") |
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if title.text and title.text.strip() != "": |
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return title.text.strip() |
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def _get_author(soup): |
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author = soup.find("author") |
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if author.text and author.text.strip() != "": |
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return author.text.strip() |
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def _get_creation(soup): |
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creation = soup.find("creation") |
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if creation.text and creation.text.strip() != "": |
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return creation.text.strip() |
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def _get_paragraphs(soup): |
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import re |
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out = [] |
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body = soup.find('body') |
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for p in body.find_all(['p', 'head']): |
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text = p.text.strip() |
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text = text.replace('\n', ' ') |
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text = re.sub(' +', ' ', text) |
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if text: |
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out.append(text) |
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return out |
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def _get_categories(text): |
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import re |
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out = [] |
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for cat in re.findall('<catRef target="([^"]+)">', text): |
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out.append(cat) |
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return out |
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def _get_pos(soup): |
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out = [] |
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for sent in soup.find_all('s'): |
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words = [] |
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for word in sent.find_all('w'): |
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if word.text: |
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text = word.text.strip() |
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msd = word.get('msd') |
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if msd and text: |
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words.append({"msd": msd, "word": text}) |
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out.append(words) |
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return out |
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