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+dataset_info: +- config_name: . + features: + - name: filename + dtype: string + - name: cik + dtype: string + - name: year + dtype: string + - name: section_1 + dtype: string + - name: section_1A + dtype: string + - name: section_1B + dtype: string + - name: section_2 + dtype: string + - name: section_3 + dtype: string + - name: section_4 + dtype: string + - name: section_5 + dtype: string + - name: section_6 + dtype: string + - name: section_7 + dtype: string + - name: section_7A + dtype: string + - name: section_8 + dtype: string + - name: section_9 + dtype: string + - name: section_9A + dtype: string + - name: section_9B + dtype: string + - name: section_10 + dtype: string + - name: section_11 + dtype: string + - name: section_12 + dtype: string + - name: section_13 + dtype: string + - name: section_14 + dtype: string + - name: section_15 + dtype: string + splits: + - name: train + num_bytes: 40306320885 + num_examples: 220375 + download_size: 10734208660 + dataset_size: 40306320885 +- config_name: full + features: + - name: filename + dtype: string + - name: cik + dtype: string + - name: year + dtype: string + - name: section_1 + dtype: string + - name: section_1A + dtype: string + - name: section_1B + dtype: string + - name: section_2 + dtype: string + - name: section_3 + dtype: string + - name: section_4 + dtype: string + - name: section_5 + dtype: string + - name: section_6 + dtype: string + - name: section_7 + dtype: string + - name: section_7A + dtype: string + - name: section_8 + dtype: string + - name: section_9 + dtype: string + - name: section_9A + dtype: string + - name: section_9B + dtype: string + - name: section_10 + dtype: string + - name: section_11 + dtype: string + - name: section_12 + dtype: string + - name: section_13 + dtype: string + - name: section_14 + dtype: string + - name: section_15 + dtype: string + splits: + - name: train + num_bytes: 32237457024 + num_examples: 176289 + - name: validation + num_bytes: 4023129683 + num_examples: 22050 + - name: test + num_bytes: 4045734178 + num_examples: 22036 + download_size: 40699852536 + dataset_size: 40306320885 +- config_name: year_1993 + features: + - name: filename + dtype: string + - name: cik + dtype: string + - name: year + dtype: string + - name: section_1 + dtype: string + - name: section_1A + dtype: string + - name: section_1B + dtype: string + - name: section_2 + dtype: string + - name: section_3 + dtype: string + - name: section_4 + dtype: string + - name: section_5 + dtype: string + - name: section_6 + dtype: string + - name: section_7 + dtype: string + - name: section_7A + dtype: string + - name: section_8 + dtype: string + - name: section_9 + dtype: string + - name: section_9A + dtype: string + - name: section_9B + dtype: string + - name: section_10 + dtype: string + - name: section_11 + dtype: string + - name: section_12 + dtype: string + - name: section_13 + dtype: string + - name: section_14 + dtype: string + - name: section_15 + dtype: string + splits: + - name: train + num_bytes: 112714537 + num_examples: 1060 + - name: validation + num_bytes: 13584432 + num_examples: 133 + - name: test + num_bytes: 14520566 + num_examples: 133 + download_size: 141862572 + dataset_size: 140819535 +- config_name: year_1994 + features: + - name: filename + dtype: string + - name: cik + dtype: string + - name: year + dtype: string + - name: section_1 + dtype: string + - name: section_1A + dtype: string + - name: section_1B + dtype: string + - name: section_2 + dtype: string + - name: section_3 + dtype: string + - name: section_4 + dtype: string + - name: section_5 + dtype: string + - name: section_6 + dtype: string + - name: section_7 + dtype: string + - name: section_7A + dtype: string + - name: section_8 + dtype: string + - name: section_9 + dtype: string + - name: section_9A + dtype: string + - name: section_9B + dtype: string + - name: section_10 + dtype: string + - name: section_11 + dtype: string + - name: section_12 + dtype: string + - name: section_13 + dtype: string + - name: section_14 + dtype: string + - name: section_15 + dtype: string + splits: + - name: train + num_bytes: 198955093 + num_examples: 2083 + - name: validation + num_bytes: 23432307 + num_examples: 261 + - name: test + num_bytes: 26115768 + num_examples: 260 + download_size: 250411041 + dataset_size: 248503168 +- config_name: year_1995 + features: + - name: filename + dtype: string + - name: cik + dtype: string + - name: year + dtype: string + - name: section_1 + dtype: string + - name: section_1A + dtype: string + - name: section_1B + dtype: string + - name: section_2 + dtype: string + - name: section_3 + dtype: string + - name: section_4 + dtype: string + - name: section_5 + dtype: string + - name: section_6 + dtype: string + - name: section_7 + dtype: string + - name: section_7A + dtype: string + - name: section_8 + dtype: string + - name: section_9 + dtype: string + - name: section_9A + dtype: string + - name: section_9B + dtype: 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181466460 + num_examples: 689 + - name: test + num_bytes: 182594965 + num_examples: 688 + download_size: 1815810567 + dataset_size: 1797470744 +- config_name: year_2019 + features: + - name: filename + dtype: string + - name: cik + dtype: string + - name: year + dtype: string + - name: section_1 + dtype: string + - name: section_1A + dtype: string + - name: section_1B + dtype: string + - name: section_2 + dtype: string + - name: section_3 + dtype: string + - name: section_4 + dtype: string + - name: section_5 + dtype: string + - name: section_6 + dtype: string + - name: section_7 + dtype: string + - name: section_7A + dtype: string + - name: section_8 + dtype: string + - name: section_9 + dtype: string + - name: section_9A + dtype: string + - name: section_9B + dtype: string + - name: section_10 + dtype: string + - name: section_11 + dtype: string + - name: section_12 + dtype: string + - name: section_13 + dtype: string + - name: section_14 + dtype: string + - name: section_15 + dtype: string + splits: + - name: train + num_bytes: 1421232269 + num_examples: 5354 + - name: validation + num_bytes: 175603562 + num_examples: 670 + - name: test + num_bytes: 176336174 + num_examples: 669 + download_size: 1791237155 + dataset_size: 1773172005 +- config_name: year_2020 + features: + - name: filename + dtype: string + - name: cik + dtype: string + - name: year + dtype: string + - name: section_1 + dtype: string + - name: section_1A + dtype: string + - name: section_1B + dtype: string + - name: section_2 + dtype: string + - name: section_3 + dtype: string + - name: section_4 + dtype: string + - name: section_5 + dtype: string + - name: section_6 + dtype: string + - name: section_7 + dtype: string + - name: section_7A + dtype: string + - name: section_8 + dtype: string + - name: section_9 + dtype: string + - name: section_9A + dtype: string + - name: section_9B + dtype: string + - name: section_10 + dtype: string + - name: section_11 + dtype: string + - name: section_12 + dtype: string + - name: section_13 + dtype: string + - name: section_14 + dtype: string + - name: section_15 + dtype: string + splits: + - name: train + num_bytes: 1541847387 + num_examples: 5480 + - name: validation + num_bytes: 193498658 + num_examples: 686 + - name: test + num_bytes: 192600298 + num_examples: 685 + download_size: 1946916132 + dataset_size: 1927946343 +annotations_creators: +- no-annotation +language: +- en +language_creators: +- other +license: +- apache-2.0 +multilinguality: +- monolingual +pretty_name: EDGAR 10K Filings +size_categories: +- 100K +**cik**: EDGAR identifier for a firm.
+**year**: Year of report.
+**section_1**: Corressponding section of the Annual Report.
+**section_1A**: Corressponding section of the Annual Report.
+**section_1B**: Corressponding section of the Annual Report.
+**section_2**: Corressponding section of the Annual Report.
+**section_3**: Corressponding section of the Annual Report.
+**section_4**: Corressponding section of the Annual Report.
+**section_5**: Corressponding section of the Annual Report.
+**section_6**: Corressponding section of the Annual Report.
+**section_7**: Corressponding section of the Annual Report.
+**section_7A**: Corressponding section of the Annual Report.
+**section_8**: Corressponding section of the Annual Report.
+**section_9**: Corressponding section of the Annual Report.
+**section_9A**: Corressponding section of the Annual Report.
+**section_9B**: Corressponding section of the Annual Report.
+**section_10**: Corressponding section of the Annual Report.
+**section_11**: Corressponding section of the Annual Report.
+**section_12**: Corressponding section of the Annual Report.
+**section_13**: Corressponding section of the Annual Report.
+**section_14**: Corressponding section of the Annual Report.
+**section_15**: Corressponding section of the Annual Report.
+ +```python +import datasets + +# Load the entire dataset +raw_dataset = datasets.load_dataset("JanosAudran/edgar_corpus", "full") + +# Load a specific year and split +raw_dataset = datasets.load_dataset("JanosAudran/edgar_corpus", "year_1993", split="train") +``` + +### Data Splits + +| Config | Training | Validation | Test | +| --------- | -------- | ---------- | ------ | +| full | 176,289 | 22,050 | 22,036 | +| year_1993 | 1,060 | 133 | 133 | +| year_1994 | 2,083 | 261 | 260 | +| year_1995 | 4,110 | 514 | 514 | +| year_1996 | 7,589 | 949 | 949 | +| year_1997 | 8,084 | 1,011 | 1,011 | +| year_1998 | 8,040 | 1,006 | 1,005 | +| year_1999 | 7,864 | 984 | 983 | +| year_2000 | 7,589 | 949 | 949 | +| year_2001 | 7,181 | 898 | 898 | +| year_2002 | 6,636 | 830 | 829 | +| year_2003 | 6,672 | 834 | 834 | +| year_2004 | 7,111 | 889 | 889 | +| year_2005 | 7,113 | 890 | 889 | +| year_2006 | 7,064 | 883 | 883 | +| year_2007 | 6,683 | 836 | 835 | +| year_2008 | 7,408 | 927 | 926 | +| year_2009 | 7,336 | 917 | 917 | +| year_2010 | 7,013 | 877 | 877 | +| year_2011 | 6,724 | 841 | 840 | +| year_2012 | 6,479 | 810 | 810 | +| year_2013 | 6,372 | 797 | 796 | +| year_2014 | 6,261 | 783 | 783 | +| year_2015 | 6,028 | 754 | 753 | +| year_2016 | 5,812 | 727 | 727 | +| year_2017 | 5,635 | 705 | 704 | +| year_2018 | 5,508 | 689 | 688 | +| year_2019 | 5,354 | 670 | 669 | +| year_2020 | 5,480 | 686 | 685 | + +## Dataset Creation + +### Source Data + +#### Initial Data Collection and Normalization + +Initial data was collected and processed by the authors of the research paper **EDGAR-CORPUS: Billions of Tokens Make The World Go Round**. + +#### Who are the source language producers? + +Public firms filing with the SEC. + +### Annotations + +#### Annotation process + +NA + +#### Who are the annotators? + +NA + +### Personal and Sensitive Information + +The dataset contains public filings data from SEC. + +## Considerations for Using the Data + +### Social Impact of Dataset + +Low to none. + +### Discussion of Biases + +The dataset is about financial information of public companies and as such the tone and style of text is in line with financial literature. + +### Other Known Limitations + +The dataset needs further cleaning for improved performance. + +## Additional Information + +### Licensing Information + +EDGAR data is publicly available. + +### References + +- Lefteris Loukas, Manos Fergadiotis, Ion Androutsopoulos, & Prodromos Malakasiotis. (2021). EDGAR-CORPUS [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5589195 + +- Loukas, Lefteris & Fergadiotis, Manos & Androutsopoulos, Ion & Malakasiotis, Prodromos. (2021). EDGAR-CORPUS: Billions of Tokens Make The World Go Round. https://arxiv.org/abs/2109.14394v2 \ No newline at end of file diff --git a/edgar_corpus.py b/edgar_corpus.py new file mode 100644 index 0000000000000000000000000000000000000000..8605530a5f95549d068f05afaedf38e0fb06290e --- /dev/null +++ b/edgar_corpus.py @@ -0,0 +1,129 @@ +# 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. +"""A dataset of 10K filings from SEC EDGAR system.""" + + +import json +import datasets + +_DESCRIPTION = """ +The dataset contains annual filings (10K) of all publicly traded firms from 1993-2020. The table data is stripped but all text is retained. +This dataset allows easy access to the EDGAR-CORPUS dataset based on the paper EDGAR-CORPUS: Billions of Tokens Make The World Go Round (See References in README.md for details). +""" + +_LICENSE = "apache-2.0" + +_VERSION = "1.0.0" + +_FEATURES = [ + "filename", + "cik", + "year", + "section_1", + "section_1A", + "section_1B", + "section_2", + "section_3", + "section_4", + "section_5", + "section_6", + "section_7", + "section_7A", + "section_8", + "section_9", + "section_9A", + "section_9B", + "section_10", + "section_11", + "section_12", + "section_13", + "section_14", + "section_15", +] + +_URLS = {"full":"", **{"year_"+str(year):str(year)+"/" for year in range(1993,2021,1)}} + +class EdgarCorpus(datasets.GeneratorBasedBuilder): + + BUILDER_CONFIGS = [ + *[datasets.BuilderConfig(name="full", version=datasets.Version(_VERSION), description="The full dataset from 1993-2020")], + *[datasets.BuilderConfig(name="year_"+str(year), version=datasets.Version(_VERSION), description="The dataset containg only the year "+str(year)) for year in range(1993, 2021, 1)] + ] + + DEFAULT_CONFIG_NAME = "full" + + def _info(self): + features = datasets.Features({item: datasets.Value("string") for item in _FEATURES}) + + return datasets.DatasetInfo( + description=_DESCRIPTION, + features=features, + license=_LICENSE + ) + + def _split_generators(self, dl_manager): + # Define splits based on the config + exclude_keys = ['full'] + if self.config.name == "full": + urls = {key: value for key, value in _URLS.items() if key not in exclude_keys} + else: + urls = {self.config.name: _URLS[self.config.name]} + + # Add test/train/validate files to url bases + urls = {k+'_'+item: v+item+'.jsonl' for item in ['train', 'test', 'validate'] for k, v in urls.items()} + + # We have the unzipped files by directory. + data_dir = dl_manager.download_and_extract(urls) + + # Create the full path to the extracted files as it can be one or multiple + filepaths = { + "test": {k: v for k, v in data_dir.items() if 'test' in k}, + "train": {k: v for k, v in data_dir.items() if 'train' in k}, + "validate": {k: v for k, v in data_dir.items() if 'validate' in k}, + } + + return [ + datasets.SplitGenerator( + name=datasets.Split.TRAIN, + # These kwargs will be passed to _generate_examples + gen_kwargs={ + "filepath": filepaths["train"], + "split": "train", + }, + ), + datasets.SplitGenerator( + name=datasets.Split.VALIDATION, + # These kwargs will be passed to _generate_examples + gen_kwargs={ + "filepath": filepaths["validate"], + "split": "validate", + }, + ), + datasets.SplitGenerator( + name=datasets.Split.TEST, + # These kwargs will be passed to _generate_examples + gen_kwargs={ + "filepath": filepaths["test"], + "split": "test" + }, + ), + ] + + # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` + def _generate_examples(self, filepath, split): + for _, path in filepath.items(): + with open(path, encoding="utf-8") as f: + for row in f: + data = json.loads(row) + yield data["filename"], {item: data[item] for item in _FEATURES} \ No newline at end of file