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CSKG.py

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-# 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.
-        with open(filepath, 'rb') as f:
-            for id_, row in enumerate(f):
-                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"],
-                #     }

README.md

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----
-license: openrail
-task_categories:
-- question-answering
-language:
-- en
----
-# Dataset Card for Dataset Name
-
-## Dataset Description
-
-- **Homepage:** 
-- **Repository:** 
-- **Paper:** 
-- **Leaderboard:** 
-- **Point of Contact:** 
-
-### Dataset Summary
-
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
-
-### Supported Tasks and Leaderboards
-
-[More Information Needed]
-
-### Languages
-
-[More Information Needed]
-
-## Dataset Structure
-
-### Data Instances
-
-[More Information Needed]
-
-### Data Fields
-
-[More Information Needed]
-
-### Data Splits
-
-[More Information Needed]
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed]
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed]
-
-#### Who are the source language producers?
-
-[More Information Needed]
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-[More Information Needed]
-
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
-
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
-
-[More Information Needed]
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed]
-
-### Licensing Information
-
-[More Information Needed]
-
-### Citation Information
-
-[More Information Needed]
-
-### Contributions
-
-[More Information Needed]

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