| """Fin-Fact dataset.""" | |
| import json | |
| import os | |
| import datasets | |
| _CITATION = """\ | |
| @misc{rangapur2023finfact, | |
| title={Fin-Fact: A Benchmark Dataset for Multimodal Financial Fact Checking and Explanation Generation}, | |
| author={Aman Rangapur and Haoran Wang and Kai Shu}, | |
| year={2023}, | |
| eprint={2309.08793}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.AI} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| Welcome to the Fin-Fact repository! Fin-Fact is a comprehensive dataset designed specifically for financial fact-checking and explanation generation. The dataset consists of 3121 claims spanning multiple financial sectors. | |
| """ | |
| _HOMEPAGE = "https://github.com/IIT-DM/Fin-Fact" | |
| _LICENSE = """\ | |
| MIT License | |
| Copyright (c) 2023 Illinois Tech Data Mining Lab | |
| Permission is hereby granted, free of charge, to any person obtaining a copy | |
| of this software and associated documentation files (the "Software"), to deal | |
| in the Software without restriction, including without limitation the rights | |
| to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
| copies of the Software, and to permit persons to whom the Software is | |
| furnished to do so, subject to the following conditions: | |
| The above copyright notice and this permission notice shall be included in all | |
| copies or substantial portions of the Software. | |
| THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | |
| IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | |
| FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | |
| AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | |
| LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | |
| OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | |
| SOFTWARE. | |
| """ | |
| _URL = "https://huggingface.co/datasets/amanrangapur/Fin-Fact/resolve/main/finfact.json" | |
| # class FinFact(datasets.GeneratorBasedBuilder): | |
| # VERSION = datasets.Version("1.0.0") | |
| # BUILDER_CONFIGS = [ | |
| # datasets.BuilderConfig( | |
| # name="finfact", | |
| # version=datasets.Version("1.0.0") | |
| # ) | |
| # ] | |
| # def _info(self): | |
| # return datasets.DatasetInfo( | |
| # description=_DESCRIPTION, | |
| # features=datasets.Features( | |
| # { | |
| # "url": datasets.Value("string"), | |
| # "claim": datasets.Value("string"), | |
| # "author": datasets.Value("string"), | |
| # "posted": datasets.Value("string"), | |
| # # "justification": datasets.Value("string"), | |
| # # "issues": datasets.Value("string"), | |
| # # "evidence": datasets.Value("string"), | |
| # # "summary": datasets.Value("string"), | |
| # # "label": datasets.Value("string"), | |
| # } | |
| # ), | |
| # supervised_keys=None, | |
| # homepage=_HOMEPAGE, | |
| # citation=_CITATION, | |
| # license=_LICENSE, | |
| # version=self.VERSION, | |
| # ) | |
| # def _split_generators(self, dl_manager): | |
| # """Returns SplitGenerators.""" | |
| # # lang = str(self.config.name) | |
| # url = _URL.format(self.VERSION.version_str[:-2]) | |
| # data_dir = dl_manager.download_and_extract(url) | |
| # return [ | |
| # datasets.SplitGenerator( | |
| # name=datasets.Split.TRAIN, | |
| # gen_kwargs={ | |
| # "filepath": os.path.join(data_dir), | |
| # }, | |
| # ) | |
| # ] | |
| # def _generate_examples(self, filepath): | |
| # """Yields examples as (key, example) tuples.""" | |
| # with open(filepath, encoding="utf-8") as f: | |
| # for idx_, row in enumerate(f): | |
| # data = json.loads(row) | |
| # yield idx_, { | |
| # "url": data["url"], | |
| # "claim": data["claim"], | |
| # "author": data["author"], | |
| # "posted": data["posted"], | |
| # # "sci_digest": data["sci_digest"], | |
| # # "justification": data["justification"], | |
| # # "issues": data["issues"], | |
| # # "image_data": data["image_data"], | |
| # # "evidence": data["evidence"], | |
| # # "label": data["label"], | |
| # } | |
| class Finfact(datasets.BuilderConfig): | |
| """BuilderConfig for Fin-Fact""" | |
| def __init__(self, **kwargs): | |
| """ | |
| Args: | |
| **kwargs: keyword arguments forwarded to super. | |
| """ | |
| super(Finfact, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs) | |
| class PubmedQA(datasets.GeneratorBasedBuilder): | |
| VERSION = datasets.Version("1.0.0") | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="finfact", | |
| version=datasets.Version("1.0.0") | |
| ) | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "url": datasets.Value("string"), | |
| "claim": datasets.Value("string"), | |
| "author": datasets.Value("string"), | |
| "posted": datasets.Value("string"), | |
| } | |
| ), | |
| supervised_keys=None, | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| downloaded_files = dl_manager.download_and_extract(_URL) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files} | |
| ) | |
| ] | |
| # def _split_generators(self, dl_manager): | |
| # """Returns SplitGenerators.""" | |
| # # lang = str(self.config.name) | |
| # url = _URL.format(self.VERSION.version_str[:-2]) | |
| # data_dir = dl_manager.download_and_extract(url) | |
| # return [ | |
| # datasets.SplitGenerator( | |
| # name=datasets.Split.TRAIN, | |
| # gen_kwargs={ | |
| # "filepath": os.path.join(data_dir), | |
| # }, | |
| # ) | |
| # ] | |
| # def _generate_examples(self, filepath): | |
| # """Yields examples as (key, example) tuples.""" | |
| # with open(filepath, encoding="utf-8") as f: | |
| # for idx_, row in enumerate(f): | |
| # data = json.loads(row) | |
| # yield idx_, { | |
| # "url": data["url"], | |
| # "claim": data["claim"], | |
| # "author": data["author"], | |
| # "posted": data["posted"], | |
| # # "sci_digest": data["sci_digest"], | |
| # # "justification": data["justification"], | |
| # # "issues": data["issues"], | |
| # # "image_data": data["image_data"], | |
| # # "evidence": data["evidence"], | |
| # # "label": data["label"], | |
| # } | |
| # def _generate_examples(self, filepath): | |
| # with open(filepath, encoding="utf-8") as f: | |
| # data = json.load(f) | |
| # print(data) | |
| # for id_, row in enumerate(data): | |
| # print("id_", id_) | |
| # print("row ", row) | |
| # yield id_, { | |
| # "url": data[row]["url"], | |
| # "claim": data[row]["claim"], | |
| # "author": data[row]["author"], | |
| # "posted": data[row]["posted"], | |
| # # "context": { | |
| # # "contexts": data[row]["CONTEXTS"], | |
| # # "labels": data[row]["LABELS"], | |
| # # "meshes": data[row]["MESHES"], | |
| # # }, | |
| # # "long_answer": data[row]["LONG_ANSWER"], | |
| # # "final_decision": data[row]["final_decision"], | |
| # } | |
| def _generate_examples(self, filepath): | |
| with open(filepath, encoding="utf-8") as f: | |
| data = json.load(f) | |
| for id_, row in enumerate(data): | |
| yield id_, { | |
| "url": row["url"], | |
| "claim": row["claim"], | |
| "author": row["author"], | |
| "posted": row["posted"], | |
| } | |