# coding=utf-8 # Copyright 2022 HuggingFace Datasets Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # Lint as: python3 """TODO""" from datetime import datetime from typing import Optional import datasets import re _CITATION = """\ TODO """ _DESCRIPTION = """\ TODO """ _BASE_URL_TRAIN_DEV_TEST = "https://raw.githubusercontent.com/impresso/CLEF-HIPE-2020/master/data/v1.4/" _URLs = { "EN": { "dev": _BASE_URL_TRAIN_DEV_TEST + "en/HIPE-data-v1.4-dev-en.tsv", "test": _BASE_URL_TRAIN_DEV_TEST + "en/HIPE-data-v1.4-test-en.tsv" }, # English only no train "DE": { "dev": _BASE_URL_TRAIN_DEV_TEST + "de/HIPE-data-v1.4-dev-de.tsv", "train": _BASE_URL_TRAIN_DEV_TEST + "de/HIPE-data-v1.4-train-de.tsv", "test": _BASE_URL_TRAIN_DEV_TEST + "de/HIPE-data-v1.4-test-de.tsv" }, "FR": { "dev": _BASE_URL_TRAIN_DEV_TEST + "fr/HIPE-data-v1.4-dev-fr.tsv", "train": _BASE_URL_TRAIN_DEV_TEST + "fr/HIPE-data-v1.4-train-fr.tsv", "test": _BASE_URL_TRAIN_DEV_TEST + "fr/HIPE-data-v1.4-test-fr.tsv" }, } class HIPE2020Config(datasets.BuilderConfig): """BuilderConfig for HIPE2020""" def __init__(self, data_urls,**kwargs): """BuilderConfig for HIPE2020. Args: **kwargs: keyword arguments forwarded to super. """ super(HIPE2020Config, self).__init__(**kwargs) self.data_urls = data_urls class HIPE2020(datasets.GeneratorBasedBuilder): """HIPE2020 dataset.""" BUILDER_CONFIGS = [ HIPE2020Config( name="en", data_urls=_URLs["EN"], version=datasets.Version("1.0.0"), description="HIPE dataset covering English", ), HIPE2020Config( name="de", data_urls=_URLs["DE"], version=datasets.Version("1.0.0"), description="HIPE dataset covering German", ), HIPE2020Config( name="fr", data_urls=_URLs["FR"], version=datasets.Version("1.0.0"), description="HIPE dataset covering French", ), ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "id": datasets.Value("string"), "tokens": datasets.Sequence(datasets.Value("string")), "NE_COARSE_LIT": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-comp", "B-loc", "B-org", "B-pers", "B-prod", "B-time", "I-loc", "I-org", "I-pers", "I-prod", "I-time", "_", ] ) ), "NE_COARSE_METO_tags": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-loc", "B-org", "B-pers", "B-prod", "B-time", "I-loc", "I-org", "I-pers", "_", ] ) ), "NE_FINE_LIT_tags": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-comp.name", "B-loc", "B-loc.add.elec", "B-loc.add.phys", "B-loc.adm.nat", "B-loc.adm.reg", "B-loc.adm.sup", "B-loc.adm.town", "B-loc.fac", "B-loc.oro", "B-loc.phys.astro", "B-loc.phys.geo", "B-loc.phys.hydro", "B-loc.unk", "B-org", "B-org.adm", "B-org.ent", "B-org.ent.pressagency", "B-pers", "B-pers.coll", "B-pers.ind", "B-pers.ind.articleauthor", "B-prod", "B-prod.doctr", "B-prod.media", "B-time", "B-time.date.abs", "I-loc", "I-loc.add.elec", "I-loc.add.phys", "I-loc.adm.nat", "I-loc.adm.reg", "I-loc.adm.sup", "I-loc.adm.town", "I-loc.fac", "I-loc.oro", "I-loc.phys.astro", "I-loc.phys.geo", "I-loc.phys.hydro", "I-loc.unk", "I-org", "I-org.adm", "I-org.ent", "I-org.ent.pressagency", "I-pers", "I-pers.coll", "I-pers.ind", "I-pers.ind.articleauthor", "I-prod", "I-prod.doctr", "I-prod.media", "I-time", "I-time.date.abs", "_", ] ) ), "NE_FINE_METO_tags": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-loc", "B-loc.adm.nat", "B-loc.adm.reg", "B-loc.adm.town", "B-loc.fac", "B-loc.oro", "B-org", "B-org.adm", "B-org.ent", "B-pers.coll", "B-pers.ind", "B-prod.media", "B-time.date.abs", "I-loc", "I-loc.adm.nat", "I-loc.adm.reg", "I-loc.fac", "I-loc.oro", "I-org", "I-org.adm", "I-org.ent", "I-pers", "I-pers.ind", "_", ] ) ), "NE_FINE_COMP_tags": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-comp.demonym", "B-comp.function", "B-comp.name", "B-comp.qualifier", "B-comp.title", "I-comp.demonym", "I-comp.function", "I-comp.name", "I-comp.qualifier", "I-comp.title", "_", ] ) ), "NE_NESTED_tags": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-loc", "B-loc.adm.nat", "B-loc.adm.reg", "B-loc.adm.sup", "B-loc.adm.town", "B-loc.fac", "B-loc.oro", "B-loc.phys.geo", "B-loc.phys.hydro", "B-org", "B-org.adm", "B-org.ent", "B-pers.coll", "B-pers.ind", "B-prod.media", "B-time.date.abs", "I-loc", "I-loc.adm.nat", "I-loc.adm.reg", "I-loc.adm.town", "I-loc.adm.sup", "I-loc.fac", "I-loc.oro", "I-loc.phys.astro", "I-loc.phys.geo", "I-loc.phys.hydro", "I-org", "I-org.adm", "I-org.ent", "I-pers.ind", "I-prod.media", "_", ] ) ), "NEL_LIT_ID": datasets.Sequence(datasets.Value("string")), "NEL_METO_ID": datasets.Sequence(datasets.Value("string")), "no_space_after": datasets.Sequence(datasets.Value("bool")), "end_of_line": datasets.Sequence(datasets.Value("bool")), "PySBDSegment":datasets.Sequence(datasets.Value("bool")), "date": datasets.Value("timestamp[s]"), "title": datasets.Value("string"), "document_id": datasets.Value("string"), } ), supervised_keys=None, homepage="TODO", citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" downloaded_files = dl_manager.download_and_extract(self.config.data_urls) data_files = { "dev": downloaded_files["dev"], "test": downloaded_files["test"], } splits = [ datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_files["dev"]}, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}, ), ] if self.config.name != "en": data_files.update({ "train": downloaded_files["train"], }) splits += [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}, ), ] return splits def _generate_examples(self, filepath): date_re = re.compile(r"# date = (\d{4}-\d{2}-\d{02})") title_re = re.compile(r"newspaper = (\w{3})") document_id_re = re.compile(r"document_id = (.*)") with open(filepath, encoding="utf-8") as f: guid = 0 tokens = [] NE_COARSE_LIT_tags = [] NE_COARSE_METO_tags = [] NE_FINE_LIT_tags = [] NE_FINE_METO_tags = [] NE_FINE_COMP_tags = [] NE_NESTED_tags = [] NEL_LIT_ID = [] NEL_METO_ID = [] no_space_after = [] end_of_line = [] pysdbsegment = [] new_sentence = False for line in f: if line.startswith( "TOKEN NE-COARSE-LIT NE-COARSE-METO NE-FINE-LIT NE-FINE-METO NE-FINE-COMP NE-NESTED NEL-LIT NEL-METO MISC" ): continue if line.startswith("#") or line == "\n": date_match = re.search(date_re, line) if date_match: date = date_match.group(1) date = datetime.strptime(date, "%Y-%m-%d") title_match = re.search(title_re, line) if title_match: title = title_match.group(1) document_id_match = re.search(document_id_re, line) if document_id_match: document_id = document_id_match.group(1) if tokens: yield guid, { "id": str(guid), "tokens": tokens, "NE_COARSE_LIT": NE_COARSE_LIT_tags, "NE_COARSE_METO_tags": NE_COARSE_METO_tags, "NE_FINE_LIT_tags": NE_FINE_LIT_tags, "NE_FINE_METO_tags": NE_FINE_METO_tags, "NE_FINE_COMP_tags": NE_FINE_COMP_tags, "NE_NESTED_tags": NE_NESTED_tags, "NEL_LIT_ID": NEL_LIT_ID, "NEL_METO_ID": NEL_METO_ID, "no_space_after": no_space_after, "end_of_line": end_of_line, "PySBDSegment":pysdbsegment, "date": date, "title": title, "document_id": document_id, } guid += 1 tokens = [] NE_COARSE_LIT_tags = [] NE_COARSE_METO_tags = [] NE_FINE_LIT_tags = [] NE_FINE_METO_tags = [] NE_FINE_COMP_tags = [] NE_NESTED_tags = [] NEL_LIT_ID = [] NEL_METO_ID = [] no_space_after = [] end_of_line = [] pysdbsegment = [] else: # New row if there is a new sentence if new_sentence == True: yield guid, { "id": str(guid), "tokens": tokens, "NE_COARSE_LIT": NE_COARSE_LIT_tags, "NE_COARSE_METO_tags": NE_COARSE_METO_tags, "NE_FINE_LIT_tags": NE_FINE_LIT_tags, "NE_FINE_METO_tags": NE_FINE_METO_tags, "NE_FINE_COMP_tags": NE_FINE_COMP_tags, "NE_NESTED_tags": NE_NESTED_tags, "NEL_LIT_ID": NEL_LIT_ID, "NEL_METO_ID": NEL_METO_ID, "no_space_after": no_space_after, "end_of_line": end_of_line, "PySBDSegment":pysdbsegment, "date": date, "title": title, "document_id": document_id, } guid += 1 tokens = [] NE_COARSE_LIT_tags = [] NE_COARSE_METO_tags = [] NE_FINE_LIT_tags = [] NE_FINE_METO_tags = [] NE_FINE_COMP_tags = [] NE_NESTED_tags = [] NEL_LIT_ID = [] NEL_METO_ID = [] no_space_after = [] end_of_line = [] pysdbsegment = [] # HIPE 2020 tokens are tab separated splits = line.split( "\t" ) # TOKEN NE-COARSE-LIT NE-COARSE-METO NE-FINE-LIT NE-FINE-METO NE-FINE-COMP NE-NESTED NEL-LIT NEL-METO MISC tokens.append(splits[0]) NE_COARSE_LIT_tags.append(splits[1]) NE_COARSE_METO_tags.append(splits[2]) NE_FINE_LIT_tags.append(splits[3]) NE_FINE_METO_tags.append(splits[4]) NE_FINE_COMP_tags.append(splits[5]) NE_NESTED_tags.append(splits[6]) NEL_LIT_ID.append(splits[7]) NEL_METO_ID.append(splits[8]) misc = splits[-1] is_space = "NoSpaceAfter" in misc is_end_of_line = "EndOfLine" in misc PySBDSegment = "PySBDSegment" in misc no_space_after.append(is_space) end_of_line.append(is_end_of_line) pysdbsegment.append(PySBDSegment) new_sentence = PySBDSegment # last example yield guid, { "id": str(guid), "tokens": tokens, "NE_COARSE_LIT": NE_COARSE_LIT_tags, "NE_COARSE_METO_tags": NE_COARSE_METO_tags, "NE_FINE_LIT_tags": NE_FINE_LIT_tags, "NE_FINE_METO_tags": NE_FINE_METO_tags, "NE_FINE_COMP_tags": NE_FINE_COMP_tags, "NE_NESTED_tags": NE_NESTED_tags, "NEL_LIT_ID": NEL_LIT_ID, "NEL_METO_ID": NEL_METO_ID, "no_space_after": no_space_after, "end_of_line": end_of_line, "PySBDSegment":pysdbsegment, "date": date, "title": title, "document_id": document_id, }