Datasets:
# 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. | |
# TODO: Address all TODOs and remove all explanatory comments | |
"""TODO: Add a description here.""" | |
import csv | |
import json | |
import os | |
import datasets | |
# TODO: Add BibTeX citation | |
# Find for instance the citation on arxiv or on the dataset repo/website | |
_CITATION = """\ | |
@article{ilievski2021cskg, | |
title={CSKG: The CommonSense Knowledge Graph}, | |
author={Ilievski, Filip and Szekely, Pedro and Zhang, Bin}, | |
journal={Extended Semantic Web Conference (ESWC)}, | |
year={2021} | |
} | |
""" | |
# TODO: Add description of the dataset here | |
# You can copy an official description | |
_DESCRIPTION = """\ | |
CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation: ATOMIC, ConceptNet, FrameNet, Roget, Visual Genome, Wikidata (We use the Wikidata-CS subset), and WordNet. CSKG is represented as a hyper-relational graph, by using the KGTK data model and file specification. Its creation is entirely supported by KGTK operations. | |
""" | |
# TODO: Add a link to an official homepage for the dataset here | |
_HOMEPAGE = "https://cskg.readthedocs.io/en/latest/" | |
# TODO: Add the licence for the dataset here if you can find it | |
_LICENSE = "Creative Commons Attribution-ShareAlike 4.0 International License" | |
# TODO: Add link to the official dataset URLs here | |
# The HuggingFace Datasets library doesn't host the datasets but only points to the original files. | |
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) | |
# _URLS = { | |
# "first_domain": "https://huggingface.co/great-new-dataset-first_domain.zip", | |
# "second_domain": "https://huggingface.co/great-new-dataset-second_domain.zip", | |
# } | |
_URLS = { | |
"cskg": "https://zenodo.org/record/4331372/files/cskg.tsv.gz", | |
} | |
# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case | |
class CSKG(datasets.GeneratorBasedBuilder): | |
"""a commonsense knowledge graph""" | |
VERSION = datasets.Version("1.1.0") | |
# This is an example of a dataset with multiple configurations. | |
# If you don't want/need to define several sub-sets in your dataset, | |
# just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes. | |
# If you need to make complex sub-parts in the datasets with configurable options | |
# You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig | |
# BUILDER_CONFIG_CLASS = MyBuilderConfig | |
# You will be able to load one or the other configurations in the following list with | |
# data = datasets.load_dataset('my_dataset', 'first_domain') | |
# data = datasets.load_dataset('my_dataset', 'second_domain') | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig(name="cskg", version=VERSION, description="The relationships defined by cskg"), | |
# datasets.BuilderConfig(name="second_domain", version=VERSION, description="This part of my dataset covers a second domain"), | |
] | |
DEFAULT_CONFIG_NAME = "cskg" # It's not mandatory to have a default configuration. Just use one if it make sense. | |
def _info(self): | |
# TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset | |
if self.config.name == "cskg": # This is the name of the configuration selected in BUILDER_CONFIGS above | |
features = datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"node1": datasets.Value("string"), | |
"relation": datasets.Value("string"), | |
"node2": datasets.Value("string"), | |
"node1;label": datasets.Value("string"), | |
"node2;label": datasets.Value("string"), | |
"relation;label": datasets.Value("string"), | |
"relation;dimension": datasets.Value("string"), | |
"source": datasets.Value("string"), | |
"sentence": datasets.Value("string"), | |
# These are the features of your dataset like images, labels ... | |
} | |
) | |
# else: # This is an example to show how to have different features for "first_domain" and "second_domain" | |
# features = datasets.Features( | |
# { | |
# "sentence": datasets.Value("string"), | |
# "option2": datasets.Value("string"), | |
# "second_domain_answer": datasets.Value("string") | |
# # These are the features of your dataset like images, labels ... | |
# } | |
# ) | |
return datasets.DatasetInfo( | |
# This is the description that will appear on the datasets page. | |
description=_DESCRIPTION, | |
# This defines the different columns of the dataset and their types | |
features=features, # Here we define them above because they are different between the two configurations | |
# If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and | |
# specify them. They'll be used if as_supervised=True in builder.as_dataset. | |
# supervised_keys=("sentence", "label"), | |
# Homepage of the dataset for documentation | |
homepage=_HOMEPAGE, | |
# License for the dataset if available | |
license=_LICENSE, | |
# Citation for the dataset | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration | |
# If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name | |
# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS | |
# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files. | |
# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive | |
urls = _URLS[self.config.name] | |
data_dir = dl_manager.download_and_extract(urls) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"filepath": data_dir, | |
"split": "train", | |
}, | |
), | |
# datasets.SplitGenerator( | |
# name=datasets.Split.VALIDATION, | |
# # These kwargs will be passed to _generate_examples | |
# gen_kwargs={ | |
# "filepath": os.path.join(data_dir, "dev.jsonl"), | |
# "split": "dev", | |
# }, | |
# ), | |
# datasets.SplitGenerator( | |
# name=datasets.Split.TEST, | |
# # These kwargs will be passed to _generate_examples | |
# gen_kwargs={ | |
# "filepath": os.path.join(data_dir, "test.jsonl"), | |
# "split": "test" | |
# }, | |
# ), | |
] | |
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
def _generate_examples(self, filepath, split): | |
# TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset. | |
# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example. | |
# jump the first row | |
with open(filepath, 'rb') as f: | |
for id_, row in enumerate(f): | |
if id_ == 0: | |
continue | |
if self.config.name == "cskg": | |
row = row.split(b"\t") | |
# Yields examples as (key, example) tuples | |
yield id_, { | |
# "sentence": data["sentence"], | |
# "option1": data["option1"], | |
# "answer": "" if split == "test" else data["answer"], | |
"id": row[0].decode("utf-8"), | |
"node1": row[1].decode("utf-8"), | |
"relation": row[2].decode("utf-8"), | |
"node2": row[3].decode("utf-8"), | |
"node1;label": row[4].decode("utf-8"), | |
"node2;label": row[5].decode("utf-8"), | |
"relation;label": row[6].decode("utf-8"), | |
"relation;dimension": row[7].decode("utf-8"), | |
"source": row[8].decode("utf-8"), | |
"sentence": row[9].decode("utf-8"), | |
} | |
# else: | |
# yield key, { | |
# "sentence": data["sentence"], | |
# "option2": data["option2"], | |
# "second_domain_answer": "" if split == "test" else data["second_domain_answer"], | |
# } |