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Co-authored-by: Parquet-converter (BOT) <parquet-converter@users.noreply.huggingface.co>
- .gitattributes +3 -0
- README.md +24 -25
- dataset_infos.json +0 -1
- gazeta_val.jsonl → default/test/0000.parquet +2 -2
- gazeta_train.jsonl → default/train/0000.parquet +2 -2
- gazeta_test.jsonl → default/train/0001.parquet +2 -2
- default/validation/0000.parquet +3 -0
- gazeta.py +0 -92
@@ -28,3 +28,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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gazeta_train.jsonl filter=lfs diff=lfs merge=lfs -text
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gazeta_val.jsonl filter=lfs diff=lfs merge=lfs -text
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gazeta_test.jsonl filter=lfs diff=lfs merge=lfs -text
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gazeta_train.jsonl filter=lfs diff=lfs merge=lfs -text
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gazeta_val.jsonl filter=lfs diff=lfs merge=lfs -text
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gazeta_test.jsonl filter=lfs diff=lfs merge=lfs -text
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default/test/index.duckdb filter=lfs diff=lfs merge=lfs -text
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default/train/index.duckdb filter=lfs diff=lfs merge=lfs -text
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@@ -18,6 +18,30 @@ multilinguality:
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source_datasets:
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- original
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paperswithcode_id: gazeta
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---
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# Dataset Card for Gazeta
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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-
- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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-
- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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@@ -138,34 +159,16 @@ When the first version of the dataset was collected, there were no other dataset
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Texts and summaries were written by journalists at [Gazeta](https://www.gazeta.ru/).
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### Annotations
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#### Annotation process
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[N/A]
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#### Who are the annotators?
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[N/A]
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-
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### Personal and Sensitive Information
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The dataset is not anonymized, so individuals' names can be found in the dataset. Information about the original author is not included in the dataset.
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## Considerations for Using the Data
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### Social Impact of Dataset
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-
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[More Information Needed]
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-
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### Discussion of Biases
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It is a dataset from a single source. Thus it has a constrained text style and event perspective.
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-
### Other Known Limitations
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-
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[More Information Needed]
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-
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## Additional Information
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### Dataset Curators
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@@ -191,7 +194,3 @@ Legal basis for distribution of the dataset: https://www.gazeta.ru/credits.shtml
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isbn="978-3-030-59082-6"
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}
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```
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-
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### Contributions
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-
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[N/A]
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source_datasets:
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- original
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paperswithcode_id: gazeta
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dataset_info:
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features:
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- name: text
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dtype: string
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- name: summary
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dtype: string
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- name: title
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dtype: string
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- name: date
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dtype: string
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes: 547118436
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num_examples: 60964
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- name: validation
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num_bytes: 55784053
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num_examples: 6369
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- name: test
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num_bytes: 60816821
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num_examples: 6793
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download_size: 332486618
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dataset_size: 663719310
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---
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# Dataset Card for Gazeta
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Discussion of Biases](#discussion-of-biases)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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## Dataset Description
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Texts and summaries were written by journalists at [Gazeta](https://www.gazeta.ru/).
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### Personal and Sensitive Information
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The dataset is not anonymized, so individuals' names can be found in the dataset. Information about the original author is not included in the dataset.
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## Considerations for Using the Data
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### Discussion of Biases
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It is a dataset from a single source. Thus it has a constrained text style and event perspective.
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## Additional Information
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### Dataset Curators
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isbn="978-3-030-59082-6"
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}
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```
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{"default": {"description": "Gazeta: Dataset for Automatic Summarization of Russian News", "citation": "\n@InProceedings{10.1007/978-3-030-59082-6_9,\n author=\"Gusev, Ilya\",\n editor=\"Filchenkov, Andrey and Kauttonen, Janne and Pivovarova, Lidia\",\n title=\"Dataset for Automatic Summarization of Russian News\",\n booktitle=\"Artificial Intelligence and Natural Language\",\n year=\"2020\",\n publisher=\"Springer International Publishing\",\n address=\"Cham\",\n pages=\"122--134\",\n isbn=\"978-3-030-59082-6\"\n}\n", "homepage": "https://github.com/IlyaGusev/gazeta", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "summary": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "date": {"dtype": "string", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "text", "output": "summary"}, "task_templates": null, "builder_name": "gazeta_dataset", "config_name": "default", "version": {"version_str": "2.0.0", "description": null, "major": 2, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 547118576, "num_examples": 60964, "dataset_name": "gazeta_dataset"}, "test": {"name": "test", "num_bytes": 60816841, "num_examples": 6793, "dataset_name": "gazeta_dataset"}, "validation": {"name": "validation", "num_bytes": 55784073, "num_examples": 6369, "dataset_name": "gazeta_dataset"}}, "download_checksums": {"gazeta_train.jsonl": {"num_bytes": 549801555, "checksum": "678ce0eab9b3026c9f3388c6f8b2e5a48c84590819e175a462cf15749bc0c60e"}, "gazeta_val.jsonl": {"num_bytes": 56064530, "checksum": "bb1e1edd75b9de85af193de473e301655f59e345be3c29ce9087326adada24fd"}, "gazeta_test.jsonl": {"num_bytes": 61115756, "checksum": "3963ca7e2313c4bb75a4140abd614e17d98199c9f03f03490ab6afb19bfbf6cf"}}, "download_size": 666981841, "post_processing_size": null, "dataset_size": 663719490, "size_in_bytes": 1330701331}}
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size 30276385
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size 22741670
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version https://git-lfs.github.com/spec/v1
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size 27825209
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@@ -1,92 +0,0 @@
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and Ilya Gusev
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Lint as: python3
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"""Gazeta: Dataset for Automatic Summarization of Russian News"""
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import json
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import os
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import datasets
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_CITATION = """
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@InProceedings{10.1007/978-3-030-59082-6_9,
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author="Gusev, Ilya",
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editor="Filchenkov, Andrey and Kauttonen, Janne and Pivovarova, Lidia",
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title="Dataset for Automatic Summarization of Russian News",
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booktitle="Artificial Intelligence and Natural Language",
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year="2020",
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publisher="Springer International Publishing",
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address="Cham",
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pages="122--134",
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isbn="978-3-030-59082-6"
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}
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"""
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_DESCRIPTION = "Dataset for automatic summarization of Russian news"
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_HOMEPAGE = "https://github.com/IlyaGusev/gazeta"
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_URLS = {
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"train": "gazeta_train.jsonl",
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"val": "gazeta_val.jsonl",
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"test": "gazeta_test.jsonl"
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}
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_DOCUMENT = "text"
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_SUMMARY = "summary"
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class GazetaDataset(datasets.GeneratorBasedBuilder):
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"""Gazeta Dataset"""
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VERSION = datasets.Version("2.0.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="default", version=VERSION, description=""),
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]
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DEFAULT_CONFIG_NAME = "default"
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def _info(self):
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features = datasets.Features(
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{
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_DOCUMENT: datasets.Value("string"),
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_SUMMARY: datasets.Value("string"),
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"title": datasets.Value("string"),
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"date": datasets.Value("string"),
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"url": datasets.Value("string")
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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supervised_keys=(_DOCUMENT, _SUMMARY),
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homepage=_HOMEPAGE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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downloaded_files = dl_manager.download_and_extract(_URLS)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["val"]}),
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]
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def _generate_examples(self, filepath):
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with open(filepath, encoding="utf-8") as f:
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for id_, row in enumerate(f):
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data = json.loads(row)
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yield id_, data
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