Datasets:
Multilinguality:
multilingual
Annotations Creators:
expert-generated
Source Datasets:
original
Tags:
License:
# coding=utf-8 | |
# Copyright 2021 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. | |
"""British Library Books Genre Dataset""" | |
import ast | |
import csv | |
from datetime import datetime | |
from typing import Dict, List | |
import datasets | |
_CITATION = """\ | |
@misc{british library_genre, | |
title={ 19th Century Books - metadata with additional crowdsourced annotations}, | |
url={https://doi.org/10.23636/BKHQ-0312}, | |
author={{British Library} and Morris, Victoria and van Strien, Daniel and Tolfo, Giorgia and Afric, Lora and Robertson, Stewart and Tiney, Patricia and Dogterom, Annelies and Wollner, Ildi}, | |
year={2021}} | |
""" | |
_DESCRIPTION = """\ | |
This dataset contains metadata for resources belonging to the British Library’s digitised printed books (18th-19th century) collection (bl.uk/collection-guides/digitised-printed-books). | |
This metadata has been extracted from British Library catalogue records. | |
The metadata held within our main catalogue is updated regularly. | |
This metadata dataset should be considered a snapshot of this metadata. | |
""" | |
_HOMEPAGE = "doi.org/10.23636/BKHQ-0312" | |
_LICENSE = "CC0 1.0 Universal Public Domain" | |
_URL = "https://bl.iro.bl.uk/downloads/36c7cd20-c8a7-4495-acbe-469b9132c6b1?locale=en" | |
common_features = { | |
"BL record ID": datasets.Value("string"), | |
"Name": datasets.Value("string"), | |
"Dates associated with name": datasets.Value("string"), | |
"Type of name": datasets.Value("string"), | |
"Role": datasets.Value("string"), | |
"All names": datasets.features.Sequence(datasets.Value("string")), | |
"Title": datasets.Value("string"), | |
"Variant titles": datasets.Value("string"), | |
"Series title": datasets.Value("string"), | |
"Number within series": datasets.Value("string"), | |
"Country of publication": datasets.Sequence(datasets.Value("string")), | |
"Place of publication": datasets.Sequence(datasets.Value("string")), | |
"Publisher": datasets.Value("string"), | |
"Date of publication": datasets.Value("string"), | |
"Edition": datasets.Value("string"), | |
"Physical description": datasets.Value("string"), | |
"Dewey classification": datasets.Value("string"), | |
"BL shelfmark": datasets.Value("string"), | |
"Topics": datasets.Value("string"), | |
"Genre": datasets.Value("string"), | |
"Languages": datasets.features.Sequence(datasets.Value("string")), | |
"Notes": datasets.Value("string"), | |
"BL record ID for physical resource": datasets.Value("string"), | |
"classification_id": datasets.Value("string"), | |
"user_id": datasets.Value("string"), | |
"subject_ids": datasets.Value("string"), | |
"annotator_date_pub": datasets.Value("string"), | |
"annotator_normalised_date_pub": datasets.Value("string"), | |
"annotator_edition_statement": datasets.Value("string"), | |
"annotator_FAST_genre_terms": datasets.Value("string"), | |
"annotator_FAST_subject_terms": datasets.Value("string"), | |
"annotator_comments": datasets.Value("string"), | |
"annotator_main_language": datasets.Value("string"), | |
"annotator_other_languages_summaries": datasets.Value("string"), | |
"annotator_summaries_language": datasets.Value("string"), | |
"annotator_translation": datasets.Value("string"), | |
"annotator_original_language": datasets.Value("string"), | |
"annotator_publisher": datasets.Value("string"), | |
"annotator_place_pub": datasets.Value("string"), | |
"annotator_country": datasets.Value("string"), | |
"annotator_title": datasets.Value("string"), | |
"Link to digitised book": datasets.Value("string"), | |
"annotated": datasets.Value("bool"), | |
} | |
raw_features = datasets.Features( | |
{ | |
**common_features, | |
**{ | |
"Type of resource": datasets.features.ClassLabel( | |
names=["Monograph", "Serial", "Monographic component part"] | |
), | |
"created_at": datasets.Value("string"), | |
"annotator_genre": datasets.Value("string"), | |
}, | |
} | |
) | |
annotated_raw_features = datasets.Features( | |
{ | |
**common_features, | |
**{ | |
"Type of resource": datasets.features.ClassLabel( | |
names=[ | |
"Monograph", | |
"Serial", | |
] | |
), | |
"created_at": datasets.Value("timestamp[s]"), | |
"annotator_genre": datasets.features.ClassLabel( | |
names=[ | |
"Fiction", | |
"Can't tell", | |
"Non-fiction", | |
"The book contains both Fiction and Non-Fiction", | |
] | |
), | |
}, | |
} | |
) | |
class BlBooksGenre(datasets.GeneratorBasedBuilder): | |
VERSION = datasets.Version("1.1.0") | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig( | |
name="title_genre_classifiction", | |
version=VERSION, | |
description="This part of my dataset covers a first domain", | |
), | |
datasets.BuilderConfig( | |
name="annotated_raw", | |
version=VERSION, | |
description="""\ | |
This version of the dataset includes all fields from the original dataset which are annotated. | |
This includes duplication from different annotators""", | |
), | |
datasets.BuilderConfig( | |
name="raw", | |
version=VERSION, | |
description="""\ | |
This version of the dataset includes all the fields from the original dataset including rows without annotation. | |
It includes duplications from different annotators""", | |
), | |
] | |
DEFAULT_CONFIG_NAME = "title_genre_classifiction" | |
def _info(self): | |
if self.config.name == "title_genre_classifiction": | |
features = datasets.Features( | |
{ | |
"BL record ID": datasets.Value("string"), | |
"title": datasets.Value("string"), | |
"label": datasets.features.ClassLabel(names=["Fiction", "Non-fiction"]), | |
} | |
) | |
if self.config.name == "annotated_raw": | |
features = annotated_raw_features | |
if self.config.name == "raw": | |
features = raw_features | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=features, | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
data_file = dl_manager.download(_URL) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"filepath": data_file, | |
"split": "train", | |
}, | |
), | |
] | |
def _parse_language(self, row: Dict) -> List[str]: | |
languages = row["Languages"] | |
if not languages: | |
return [] | |
return languages.split(";") | |
def _parse_country(self, row: Dict) -> List[str]: | |
return row["Country of publication"].split(";") if row["Country of publication"] else [] | |
def _parse_place_of_publication(self, row: Dict) -> List[str]: | |
return row["Place of publication"].split(";") if row["Place of publication"] else [] | |
def _parse_all_names(self, row: Dict) -> List[str]: | |
return row["All names"].split(";") if row["All names"] else [] | |
def _generate_examples(self, filepath, split): | |
"""Yields examples as (key, example) tuples.""" | |
with open(filepath, encoding="utf-8") as f: | |
reader = csv.DictReader(f) | |
if self.config.name == "title_genre_classifiction": | |
unique = set() | |
id_ = 0 | |
for row in reader: | |
annotated = ast.literal_eval(row["annotated"]) | |
if not annotated: | |
continue | |
label = row["annotator_genre"] | |
if label not in {"Fiction", "Non-fiction"}: | |
continue | |
title = row["Title"] | |
if title in unique: | |
continue | |
unique.add(title) | |
id_ += 1 | |
yield id_, { | |
"BL record ID": row["BL record ID"], | |
"title": title, | |
"label": label, | |
} | |
if self.config.name == "annotated_raw": | |
id_ = 0 | |
for row in reader: | |
annotated = ast.literal_eval(row["annotated"]) | |
if not annotated: | |
continue | |
created_at = datetime.strptime(row["created_at"], "%Y-%m-%d %H:%M:%S %Z") | |
id_ += 1 | |
yield id_, { | |
"BL record ID": row["BL record ID"], | |
"Type of resource": row["Type of resource"], | |
"Name": row["Name"], | |
"Dates associated with name": row["Dates associated with name"], | |
"Type of name": row["Type of name"], | |
"Role": row["Role"], | |
"All names": self._parse_all_names(row), | |
"Title": row["Title"], | |
"Variant titles": row["Variant titles"], | |
"Series title": row["Series title"], | |
"Number within series": row["Number within series"], | |
"Country of publication": self._parse_country(row), | |
"Place of publication": self._parse_place_of_publication(row), | |
"Publisher": row["Publisher"], | |
"Date of publication": row["Date of publication"], | |
"Edition": row["Edition"], | |
"Physical description": row["Physical description"], | |
"Dewey classification": row["Dewey classification"], | |
"BL shelfmark": row["BL shelfmark"], | |
"Topics": row["Topics"], | |
"Genre": row["Genre"], | |
"Languages": self._parse_language(row), | |
"Notes": row["Notes"], | |
"BL record ID for physical resource": row["BL record ID for physical resource"], | |
"classification_id": row["classification_id"], | |
"user_id": row["user_id"], | |
"created_at": created_at, | |
"subject_ids": row["subject_ids"], | |
"annotator_date_pub": row["annotator_date_pub"], | |
"annotator_normalised_date_pub": row["annotator_normalised_date_pub"], | |
"annotator_edition_statement": row["annotator_edition_statement"], | |
"annotator_genre": row["annotator_genre"], | |
"annotator_FAST_genre_terms": row["annotator_FAST_genre_terms"], | |
"annotator_FAST_subject_terms": row["annotator_FAST_subject_terms"], | |
"annotator_comments": row["annotator_comments"], | |
"annotator_main_language": row["annotator_main_language"], | |
"annotator_other_languages_summaries": row["annotator_other_languages_summaries"], | |
"annotator_summaries_language": row["annotator_summaries_language"], | |
"annotator_translation": row["annotator_translation"], | |
"annotator_original_language": row["annotator_original_language"], | |
"annotator_publisher": row["annotator_publisher"], | |
"annotator_place_pub": row["annotator_place_pub"], | |
"annotator_country": row["annotator_country"], | |
"annotator_title": row["annotator_title"], | |
"Link to digitised book": row["Link to digitised book"], | |
"annotated": annotated, | |
} | |
if self.config.name == "raw": | |
for id_, row in enumerate(reader): | |
yield id_, { | |
"BL record ID": row["BL record ID"], | |
"Type of resource": row["Type of resource"], | |
"Name": row["Name"], | |
"Dates associated with name": row["Dates associated with name"], | |
"Type of name": row["Type of name"], | |
"Role": row["Role"], | |
"All names": self._parse_all_names(row), | |
"Title": row["Title"], | |
"Variant titles": row["Variant titles"], | |
"Series title": row["Series title"], | |
"Number within series": row["Number within series"], | |
"Country of publication": self._parse_country(row), | |
"Place of publication": self._parse_place_of_publication(row), | |
"Publisher": row["Publisher"], | |
"Date of publication": row["Date of publication"], | |
"Edition": row["Edition"], | |
"Physical description": row["Physical description"], | |
"Dewey classification": row["Dewey classification"], | |
"BL shelfmark": row["BL shelfmark"], | |
"Topics": row["Topics"], | |
"Genre": row["Genre"], | |
"Languages": self._parse_language(row), | |
"Notes": row["Notes"], | |
"BL record ID for physical resource": row["BL record ID for physical resource"], | |
"classification_id": row["classification_id"], | |
"user_id": row["user_id"], | |
"created_at": row["created_at"], | |
"subject_ids": row["subject_ids"], | |
"annotator_date_pub": row["annotator_date_pub"], | |
"annotator_normalised_date_pub": row["annotator_normalised_date_pub"], | |
"annotator_edition_statement": row["annotator_edition_statement"], | |
"annotator_genre": row["annotator_genre"], | |
"annotator_FAST_genre_terms": row["annotator_FAST_genre_terms"], | |
"annotator_FAST_subject_terms": row["annotator_FAST_subject_terms"], | |
"annotator_comments": row["annotator_comments"], | |
"annotator_main_language": row["annotator_main_language"], | |
"annotator_other_languages_summaries": row["annotator_other_languages_summaries"], | |
"annotator_summaries_language": row["annotator_summaries_language"], | |
"annotator_translation": row["annotator_translation"], | |
"annotator_original_language": row["annotator_original_language"], | |
"annotator_publisher": row["annotator_publisher"], | |
"annotator_place_pub": row["annotator_place_pub"], | |
"annotator_country": row["annotator_country"], | |
"annotator_title": row["annotator_title"], | |
"Link to digitised book": row["Link to digitised book"], | |
"annotated": ast.literal_eval(row["annotated"]), | |
} | |