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import conllu |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = "" |
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BY_NAME = "by_name" |
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BY_TYPE = "by_type" |
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TAGSET_NKJP = "nkjp" |
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TAGSET_UD = "ud" |
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EXTENSION_CONLL = "conll" |
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EXTENSION_CONLLU = "conllu" |
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EXTENSION_CONLL_SPACE_AFTER = "conll_space_after" |
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_EXTENSIONS = [EXTENSION_CONLL, EXTENSION_CONLLU, EXTENSION_CONLL_SPACE_AFTER] |
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_DESCRIPTION = { |
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BY_NAME: { |
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TAGSET_NKJP: "NLPrePL divided by document name for NKJP tagset", |
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TAGSET_UD: "NLPrePL divided by document name for UD tagset" |
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}, |
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BY_TYPE: { |
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TAGSET_NKJP: "NLPrePL divided by document type for NKJP tagset", |
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TAGSET_UD: "NLPrePL divided by document type for UD tagset" |
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} |
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} |
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_TYPES = [BY_NAME, BY_TYPE] |
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_TAGSETS = [TAGSET_NKJP, TAGSET_UD] |
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_URLS = { |
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BY_NAME: { |
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EXTENSION_CONLLU: { |
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TAGSET_NKJP: { |
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'train': "nkjp_tagset/fair_by_document_name/_conllu/train_nlprepl-nkjp.conllu.gz", |
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'dev': "nkjp_tagset/fair_by_document_name/_conllu/dev_nlprepl-nkjp.conllu.gz", |
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'test': "nkjp_tagset/fair_by_document_name/_conllu/test_nlprepl-nkjp.conllu.gz" |
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}, |
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TAGSET_UD: { |
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'train': "ud_tagset/fair_by_document_name/_conllu/train_nlprepl-ud.conllu.gz", |
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'dev': "ud_tagset/fair_by_document_name/_conllu/dev_nlprepl-ud.conllu.gz", |
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'test': "ud_tagset/fair_by_document_name/_conllu/test_nlprepl-ud.conllu.gz" |
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} |
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}, |
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EXTENSION_CONLL: { |
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TAGSET_NKJP: { |
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'train': "nkjp_tagset/fair_by_document_name/_conll/train_nlprepl-nkjp.conll.gz", |
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'dev': "nkjp_tagset/fair_by_document_name/_conll/dev_nlprepl-nkjp.conll.gz", |
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'test': "nkjp_tagset/fair_by_document_name/_conll/test_nlprepl-nkjp.conll.gz" |
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} |
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}, |
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EXTENSION_CONLL_SPACE_AFTER: { |
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TAGSET_NKJP: { |
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'train': "nkjp_tagset/fair_by_document_name/_conll_space_after/multiword_space_after_train_nlprepl-nkjp.conll.gz", |
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'dev': "nkjp_tagset/fair_by_document_name/_conll_space_after/multiword_space_after_dev_nlprepl-nkjp.conll.gz", |
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'test': "nkjp_tagset/fair_by_document_name/_conll_space_after/multiword_space_after_test_nlprepl-nkjp.conll.gz" |
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} |
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}, |
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}, |
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BY_TYPE: { |
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EXTENSION_CONLLU: { |
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TAGSET_NKJP: { |
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'train': "nkjp_tagset/fair_by_document_type/_conllu/train_nlprepl-nkjp.conllu.gz", |
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'dev': "nkjp_tagset/fair_by_document_type/_conllu/dev_nlprepl-nkjp.conllu.gz", |
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'test': "nkjp_tagset/fair_by_document_type/_conllu/test_nlprepl-nkjp.conllu.gz" |
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}, |
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TAGSET_UD: { |
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'train': "ud_tagset/fair_by_document_type/_conllu/train_nlprepl-ud.conllu.gz", |
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'dev': "ud_tagset/fair_by_document_type/_conllu/dev_nlprepl-ud.conllu.gz", |
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'test': "ud_tagset/fair_by_document_type/_conllu/test_nlprepl-ud.conllu.gz" |
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} |
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}, |
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EXTENSION_CONLL: { |
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TAGSET_NKJP: { |
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'train': "nkjp_tagset/fair_by_document_type/_conll/train_nlprepl-nkjp.conll.gz", |
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'dev': "nkjp_tagset/fair_by_document_type/_conll/dev_nlprepl-nkjp.conll.gz", |
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'test': "nkjp_tagset/fair_by_document_type/_conll/test_nlprepl-nkjp.conll.gz" |
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} |
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}, |
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EXTENSION_CONLL_SPACE_AFTER: { |
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TAGSET_NKJP: { |
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'train': "nkjp_tagset/fair_by_document_type/_conllu_space_after/multiword_space_after_train_nlprepl-nkjp.conll.gz", |
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'dev': "nkjp_tagset/fair_by_document_type/_conllu_space_after/multiword_space_after_dev_nlprepl-nkjp.conll.gz", |
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'test': "nkjp_tagset/fair_by_document_type/_conllu_space_after/multiword_space_after_test_nlprepl-nkjp.conll.gz" |
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} |
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}, |
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} |
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} |
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class NLPrePLConfig(datasets.BuilderConfig): |
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"""BuilderConfig for NKJP1M""" |
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def __init__(self, tagset: str, extension: str, **kwargs): |
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"""BuilderConfig forNKJP1M. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(NLPrePLConfig, self).__init__(**kwargs) |
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self.tagset = tagset |
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self.extension = extension |
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class NLPrePL(datasets.GeneratorBasedBuilder): |
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"""NLPrePL dataset generator.""" |
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BUILDER_CONFIGS = [ |
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NLPrePLConfig( |
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name=t + "-" + tagset + "-" + extension, |
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version=datasets.Version("1.0.0"), |
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tagset=tagset, |
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extension=extension, |
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description=_DESCRIPTION[t] |
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) |
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for t in _URLS.keys() for extension in _URLS[t].keys() for tagset in _URLS[t][extension].keys() |
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] |
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def _info(self): |
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"""Informative function about dataset features""" |
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dataset, tagset, extension = self.config.name.split("-") |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION[dataset][tagset], |
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features=datasets.Features( |
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{ |
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"sent_id": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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"orig_file_sentence": datasets.Value("string"), |
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"id": datasets.Value("string"), |
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"tokens": datasets.Sequence(datasets.Value("string")), |
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"lemmas": datasets.Sequence(datasets.Value("string")), |
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"upos": datasets.Sequence(datasets.Value("string")), |
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"xpos": datasets.Sequence(datasets.Value("string")), |
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"feats": datasets.Sequence(datasets.Value("string")), |
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"head": datasets.Sequence(datasets.Value("string")), |
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"deprel": datasets.Sequence(datasets.Value("string")), |
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"deps": datasets.Sequence(datasets.Value("string")), |
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"misc": datasets.Sequence(datasets.Value("string")), |
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} |
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), |
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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 for train, dev, and test splits.""" |
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dataset, tagset, extension = self.config.name.split("-") |
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urls = _URLS[dataset][extension][tagset] |
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downloaded_files = 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={"filepath": downloaded_files["train"]}), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={"filepath": downloaded_files["dev"]}), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"filepath": downloaded_files["test"]}), |
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] |
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def _generate_examples(self, filepath: str): |
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"""Function to generate example datapoints for the dataset.""" |
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def generate_misc_column(misc_content: dict): |
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"""Helper function that creates proper formatting for MISC column from conllu file.""" |
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if misc_content is None: |
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return "" |
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else: |
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return "|".join([k + "=" + v for k, v in misc_content.items()]) |
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id = 0 |
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logger.info("⏳ Generating examples from = %s", filepath) |
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print("Cached PATHS -- copy into STEP 5:", filepath) |
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with open(filepath, 'r', encoding="utf-8") as f: |
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tokenlist = list(conllu.parse_incr(f)) |
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for sent in tokenlist: |
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if "sent_id" in sent.metadata: |
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idx = sent.metadata["sent_id"] |
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else: |
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idx = id |
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tokens = [token["form"] for token in sent] |
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if "text" in sent.metadata: |
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txt = sent.metadata["text"] |
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else: |
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txt = " ".join(tokens) |
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yield id, { |
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"sent_id": str(idx), |
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"text": txt, |
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"orig_file_sentence": sent.metadata["orig_file_sentence"], |
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"id": [token["id"] for token in sent], |
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"tokens": [token["form"] for token in sent], |
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"lemmas": [token["lemma"] for token in sent], |
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"upos": [token["upos"] for token in sent], |
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"xpos": [token["xpos"] for token in sent], |
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"feats": [str(token["feats"]) for token in sent], |
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"head": [str(token["head"]) for token in sent], |
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"deprel": [str(token["deprel"]) for token in sent], |
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"deps": [str(token["deps"]) for token in sent], |
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"misc": [generate_misc_column(token["misc"]) for token in sent], |
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} |
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id += 1 |
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