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"], | |
| # } |