# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # 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. import os import datasets import glob import xml.etree.ElementTree as ET _CITATION = """@article{Howard2017, author = "Sharon Howard", title = "{Old Bailey Online XML Data}", year = "2017", month = "4", url = "https://figshare.shef.ac.uk/articles/dataset/Old_Bailey_Online_XML_Data/4775434", doi = "10.15131/shef.data.4775434.v2" } """ _DESCRIPTION = """The dataset consists of 2,163 transcriptions of the Proceedings and 475 Ordinary's Accounts marked up in TEI-XML, and contains some documentation covering the data structure and variables. Each Proceedings file represents one session of the court (1674-1913), and each Ordinary's Account file represents a single pamphlet (1676-1772) """ _HOMEPAGE = "https://www.dhi.ac.uk/projects/old-bailey/" _DATASETNAME = "old_bailey_proceedings" _LICENSE = "Creative Commons Attribution 4.0 International" _URLS = { _DATASETNAME: "https://www.dhi.ac.uk/san/data/oldbailey/oldbailey.zip", } logger = datasets.utils.logging.get_logger(__name__) class OldBaileyProceedings(datasets.GeneratorBasedBuilder): """The dataset consists of 2,163 transcriptions of the Proceedings and 475 Ordinary's Accounts marked up in TEI-XML, and contains some documentation covering the data structure and variables. Each Proceedings file represents one session of the court (1674-1913), and each Ordinary's Account file represents a single pamphlet (1676-1772)""" VERSION = datasets.Version("7.2.0") def _info(self): features = datasets.Features( { "id": datasets.Value("string"), "text": datasets.Value("string"), "places": datasets.Sequence(datasets.Value("string")), "type": datasets.Value("string"), "persons": datasets.Sequence(datasets.Value("string")), "date": datasets.Value("string"), } ) return datasets.DatasetInfo( description=_DESCRIPTION, features=features, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager): urls = _URLS[_DATASETNAME] data_dir = dl_manager.download_and_extract(urls) oa_dir = "ordinarysAccounts" obp_dir = "sessionsPapers" return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_dirs": { "OA": os.path.join(data_dir, oa_dir), "OBP": os.path.join(data_dir, obp_dir), }, }, ), ] def convert_text_to_features(self, file, key): if key == "OA": root_tag = "p" else: root_tag = "div1/p" try: xml_data = ET.parse(file) root = xml_data.getroot() start = root.find("./text/body/div0") id = start.attrib["id"] date = start.find("interp[@type='date']").attrib["value"] text_parts = [] places, persons = [], [] for content in start.findall(root_tag): for place in content.findall("placeName"): if place.text: place_name = place.text.replace("\n", "").strip() if place_name: places.append(place.text) for person in content.findall("persName"): full_name = [] for name_part in person.itertext(): name_part = ( name_part.replace("\n", "").replace("\t", "").strip() ) if name_part: full_name.append(name_part) if full_name: persons.append(" ".join(full_name)) for text_snippet in content.itertext(): text_snippet = ( text_snippet.replace("\n", "").replace("\t", "").strip() ) if text_snippet: text_parts.append(text_snippet) full_text = " ".join(text_parts) return 0, { "id": id, "date": date, "type": key, "places": places, "persons": persons, "text": full_text, } except Exception as e: return -1, repr(e) def _generate_examples(self, data_dirs): for key, data_dir in data_dirs.items(): for file in glob.glob(os.path.join(data_dir, "*.xml")): status_code, ret_val = self.convert_text_to_features(file, key) if status_code: logger.warn(f"{file}:{ret_val}") input() continue else: yield ret_val["id"], ret_val