Add license and point of contact to big_patent dataset (#4269)

* Add license and point of contact to big_patent dataset

* Update metadata JSON

Commit from https://github.com/huggingface/datasets/commit/4a001dce0db53888a3554f2e2fcb97e6a36d6327

README.md

@@ -6,7 +6,7 @@ language_creators:
 languages:
 - en
 licenses:
-- unknown
+- cc-by-4-0
 multilinguality:
 - monolingual
 size_categories:
@@ -72,7 +72,7 @@ pretty_name: Big Patent
 - **Repository:**
 - **Paper:** [BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization](https://arxiv.org/abs/1906.03741)
 - **Leaderboard:**
-- **Point of Contact:**
+- **Point of Contact:** [Lu Wang](mailto:[email protected])
 
 ### Dataset Summary
 

big_patent.py

@@ -51,6 +51,8 @@ There are two features:
   - abstract: Patent abastract.
 """
 
+_LICENSE = "Creative Commons Attribution 4.0 International"
+
 _REPO = "https://huggingface.co/datasets/big_patent/resolve/main/data"
 _URLS = {
     "train": f"{_REPO}/train.zip",
@@ -121,6 +123,7 @@ class BigPatent(datasets.GeneratorBasedBuilder):
             features=datasets.Features({_DOCUMENT: datasets.Value("string"), _SUMMARY: datasets.Value("string")}),
             supervised_keys=(_DOCUMENT, _SUMMARY),
             homepage=_HOMEPAGE,
+            license=_LICENSE,
             citation=_CITATION,
         )
 

dataset_infos.json

@@ -1 +1 @@
-{"all": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "all", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 23363518650, "num_examples": 1207222, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 1290154487, "num_examples": 67068, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 1296234391, "num_examples": 67072, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 25949907528, "size_in_bytes": 32397129082}, "a": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "a", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3329778447, "num_examples": 174134, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 184116486, "num_examples": 9674, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 185987552, "num_examples": 9675, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 3699882485, "size_in_bytes": 10147104039}, "b": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "b", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2574594655, "num_examples": 161520, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 143029380, "num_examples": 8973, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 140741033, "num_examples": 8974, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 2858365068, "size_in_bytes": 9305586622}, "c": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "c", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2641973267, "num_examples": 101042, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 145441704, "num_examples": 5613, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 149052258, "num_examples": 5614, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 2936467229, "size_in_bytes": 9383688783}, "d": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "d", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 160467163, "num_examples": 10164, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 8667961, "num_examples": 565, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 8713720, "num_examples": 565, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 177848844, "size_in_bytes": 6625070398}, "e": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "e", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 535567259, "num_examples": 34443, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 28549964, "num_examples": 1914, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 29843613, "num_examples": 1914, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 593960836, "size_in_bytes": 7041182390}, "f": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "f", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1297707404, "num_examples": 85568, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 72367466, "num_examples": 4754, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 71676041, "num_examples": 4754, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 1441750911, "size_in_bytes": 7888972465}, "g": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "g", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5571186559, "num_examples": 258935, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 309182447, "num_examples": 14385, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 310624265, "num_examples": 14386, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 6190993271, "size_in_bytes": 12638214825}, "h": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. 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There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "Creative Commons Attribution 4.0 International", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "d", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 160467163, "num_examples": 10164, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 8667961, "num_examples": 565, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 8713720, "num_examples": 565, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 177848844, "size_in_bytes": 6625070398}, "e": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "Creative Commons Attribution 4.0 International", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "e", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 535567259, "num_examples": 34443, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 28549964, "num_examples": 1914, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 29843613, "num_examples": 1914, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 593960836, "size_in_bytes": 7041182390}, "f": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "Creative Commons Attribution 4.0 International", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "f", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1297707404, "num_examples": 85568, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 72367466, "num_examples": 4754, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 71676041, "num_examples": 4754, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 1441750911, "size_in_bytes": 7888972465}, "g": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "Creative Commons Attribution 4.0 International", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "g", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5571186559, "num_examples": 258935, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 309182447, "num_examples": 14385, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 310624265, "num_examples": 14386, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 6190993271, "size_in_bytes": 12638214825}, "h": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "Creative Commons Attribution 4.0 International", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "h", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4988365946, "num_examples": 257019, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 275293153, "num_examples": 14279, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 274505113, "num_examples": 14279, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 5538164212, "size_in_bytes": 11985385766}, "y": {"description": "\nBIGPATENT, consisting of 1.3 million records of U.S. patent documents\nalong with human written abstractive summaries.\nEach US patent application is filed under a Cooperative Patent Classification\n(CPC) code. There are nine such classification categories:\nA (Human Necessities), B (Performing Operations; Transporting),\nC (Chemistry; Metallurgy), D (Textiles; Paper), E (Fixed Constructions),\nF (Mechanical Engineering; Lightning; Heating; Weapons; Blasting),\nG (Physics), H (Electricity), and\nY (General tagging of new or cross-sectional technology)\nThere are two features:\n  - description: detailed description of patent.\n  - abstract: Patent abastract.\n", "citation": "\n@misc{sharma2019bigpatent,\n    title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},\n    author={Eva Sharma and Chen Li and Lu Wang},\n    year={2019},\n    eprint={1906.03741},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://evasharma.github.io/bigpatent/", "license": "Creative Commons Attribution 4.0 International", "features": {"description": {"dtype": "string", "id": null, "_type": "Value"}, "abstract": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "description", "output": "abstract"}, "task_templates": null, "builder_name": "big_patent", "config_name": "y", "version": "1.0.0", "splits": {"train": {"name": "train", "num_bytes": 2263877990, "num_examples": 124397, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 123505958, "num_examples": 6911, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 125090828, "num_examples": 6911, "dataset_name": "big_patent"}}, "download_checksums": {"https://huggingface.co/datasets/big_patent/resolve/main/data/train.zip": {"num_bytes": 5802341237, "checksum": "89831e047474822ff7be521707e9a58bd9acd4d359a194cc564e74012a44185d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/val.zip": {"num_bytes": 321731760, "checksum": "c8a3c745cac4216bd32a54149dbc044ea397e405a08b230041a554e3eb75080d"}, "https://huggingface.co/datasets/big_patent/resolve/main/data/test.zip": {"num_bytes": 323148557, "checksum": "ce605cafb69b1757276326c51d18a1c09275b1911252dd95e8e0dcbf386d1b77"}}, "download_size": 6447221554, "post_processing_size": null, "dataset_size": 2512474776, "size_in_bytes": 8959696330}}