Datasets:
big_patent

- {"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": "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": "all", "version": "2.1.2", "splits": {"train": {"name": "train", "num_bytes": 38367048389, "num_examples": 1207222, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 2115827002, "num_examples": 67068, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 2129505280, "num_examples": 67072, "dataset_name": "big_patent"}}, "download_checksums": {"data/2.1.2/train.zip": {"num_bytes": 9129045386, "checksum": "59cae1439b01102faa5b9e1bb3061867ba292a6093cf66ee3d1bc33030d7a91f"}, "data/2.1.2/val.zip": {"num_bytes": 506259325, "checksum": "9206de008607095bdb29f405ef9b525565556860d015cbd4261154644b51ce9b"}, "data/2.1.2/test.zip": {"num_bytes": 507619065, "checksum": "614821d8d8c92451ba495e0b381f157a0e0b36977a70f2d4cb3ae4b6b706539a"}}, "download_size": 10142923776, "post_processing_size": null, "dataset_size": 42612380671, "size_in_bytes": 52755304447}, "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": "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": "a", "version": "2.1.2", "splits": {"train": {"name": "train", "num_bytes": 5683460620, "num_examples": 174134, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 313324505, "num_examples": 9674, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 316633277, "num_examples": 9675, "dataset_name": "big_patent"}}, "download_checksums": {"data/2.1.2/train.zip": {"num_bytes": 9129045386, "checksum": "59cae1439b01102faa5b9e1bb3061867ba292a6093cf66ee3d1bc33030d7a91f"}, "data/2.1.2/val.zip": {"num_bytes": 506259325, "checksum": "9206de008607095bdb29f405ef9b525565556860d015cbd4261154644b51ce9b"}, "data/2.1.2/test.zip": {"num_bytes": 507619065, "checksum": "614821d8d8c92451ba495e0b381f157a0e0b36977a70f2d4cb3ae4b6b706539a"}}, "download_size": 10142923776, "post_processing_size": null, "dataset_size": 6313418402, "size_in_bytes": 16456342178}, "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": "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": "b", "version": "2.1.2", "splits": {"train": {"name": "train", "num_bytes": 4236070976, "num_examples": 161520, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 234425138, "num_examples": 8973, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 231538734, "num_examples": 8974, "dataset_name": "big_patent"}}, "download_checksums": {"data/2.1.2/train.zip": {"num_bytes": 9129045386, "checksum": "59cae1439b01102faa5b9e1bb3061867ba292a6093cf66ee3d1bc33030d7a91f"}, "data/2.1.2/val.zip": {"num_bytes": 506259325, "checksum": "9206de008607095bdb29f405ef9b525565556860d015cbd4261154644b51ce9b"}, "data/2.1.2/test.zip": {"num_bytes": 507619065, "checksum": "614821d8d8c92451ba495e0b381f157a0e0b36977a70f2d4cb3ae4b6b706539a"}}, "download_size": 10142923776, "post_processing_size": null, "dataset_size": 4702034848, "size_in_bytes": 14844958624}, "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": "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": "c", "version": "2.1.2", "splits": {"train": {"name": "train", "num_bytes": 4506249306, "num_examples": 101042, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 244684775, "num_examples": 5613, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 252566793, "num_examples": 5614, "dataset_name": "big_patent"}}, "download_checksums": {"data/2.1.2/train.zip": {"num_bytes": 9129045386, "checksum": "59cae1439b01102faa5b9e1bb3061867ba292a6093cf66ee3d1bc33030d7a91f"}, "data/2.1.2/val.zip": {"num_bytes": 506259325, "checksum": "9206de008607095bdb29f405ef9b525565556860d015cbd4261154644b51ce9b"}, "data/2.1.2/test.zip": {"num_bytes": 507619065, "checksum": "614821d8d8c92451ba495e0b381f157a0e0b36977a70f2d4cb3ae4b6b706539a"}}, "download_size": 10142923776, "post_processing_size": null, "dataset_size": 5003500874, "size_in_bytes": 15146424650}, "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": "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": "2.1.2", "splits": {"train": {"name": "train", "num_bytes": 264717412, "num_examples": 10164, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 14560482, "num_examples": 565, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 14403430, "num_examples": 565, "dataset_name": "big_patent"}}, "download_checksums": {"data/2.1.2/train.zip": {"num_bytes": 9129045386, "checksum": "59cae1439b01102faa5b9e1bb3061867ba292a6093cf66ee3d1bc33030d7a91f"}, "data/2.1.2/val.zip": {"num_bytes": 506259325, "checksum": "9206de008607095bdb29f405ef9b525565556860d015cbd4261154644b51ce9b"}, "data/2.1.2/test.zip": {"num_bytes": 507619065, "checksum": "614821d8d8c92451ba495e0b381f157a0e0b36977a70f2d4cb3ae4b6b706539a"}}, "download_size": 10142923776, "post_processing_size": null, "dataset_size": 293681324, "size_in_bytes": 10436605100}, "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": "2.1.2", "splits": {"train": {"name": "train", "num_bytes": 881101433, "num_examples": 34443, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 48646158, "num_examples": 1914, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 48586429, "num_examples": 1914, "dataset_name": "big_patent"}}, "download_checksums": {"data/2.1.2/train.zip": {"num_bytes": 9129045386, "checksum": "59cae1439b01102faa5b9e1bb3061867ba292a6093cf66ee3d1bc33030d7a91f"}, "data/2.1.2/val.zip": {"num_bytes": 506259325, "checksum": "9206de008607095bdb29f405ef9b525565556860d015cbd4261154644b51ce9b"}, "data/2.1.2/test.zip": {"num_bytes": 507619065, "checksum": "614821d8d8c92451ba495e0b381f157a0e0b36977a70f2d4cb3ae4b6b706539a"}}, "download_size": 10142923776, "post_processing_size": null, "dataset_size": 978334020, "size_in_bytes": 11121257796}, "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": "2.1.2", "splits": {"train": {"name": "train", "num_bytes": 2146383473, "num_examples": 85568, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 119632631, "num_examples": 4754, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 119596303, "num_examples": 4754, "dataset_name": "big_patent"}}, "download_checksums": {"data/2.1.2/train.zip": {"num_bytes": 9129045386, "checksum": "59cae1439b01102faa5b9e1bb3061867ba292a6093cf66ee3d1bc33030d7a91f"}, "data/2.1.2/val.zip": {"num_bytes": 506259325, "checksum": "9206de008607095bdb29f405ef9b525565556860d015cbd4261154644b51ce9b"}, "data/2.1.2/test.zip": {"num_bytes": 507619065, "checksum": "614821d8d8c92451ba495e0b381f157a0e0b36977a70f2d4cb3ae4b6b706539a"}}, "download_size": 10142923776, "post_processing_size": null, "dataset_size": 2385612407, "size_in_bytes": 12528536183}, "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": "2.1.2", "splits": {"train": {"name": "train", "num_bytes": 8877854206, "num_examples": 258935, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 492581177, "num_examples": 14385, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 496324853, "num_examples": 14386, "dataset_name": "big_patent"}}, "download_checksums": {"data/2.1.2/train.zip": {"num_bytes": 9129045386, "checksum": "59cae1439b01102faa5b9e1bb3061867ba292a6093cf66ee3d1bc33030d7a91f"}, "data/2.1.2/val.zip": {"num_bytes": 506259325, "checksum": "9206de008607095bdb29f405ef9b525565556860d015cbd4261154644b51ce9b"}, "data/2.1.2/test.zip": {"num_bytes": 507619065, "checksum": "614821d8d8c92451ba495e0b381f157a0e0b36977a70f2d4cb3ae4b6b706539a"}}, "download_size": 10142923776, "post_processing_size": null, "dataset_size": 9866760236, "size_in_bytes": 20009684012}, "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": "2.1.2", "splits": {"train": {"name": "train", "num_bytes": 8075621958, "num_examples": 257019, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 447602356, "num_examples": 14279, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 445460513, "num_examples": 14279, "dataset_name": "big_patent"}}, "download_checksums": {"data/2.1.2/train.zip": {"num_bytes": 9129045386, "checksum": "59cae1439b01102faa5b9e1bb3061867ba292a6093cf66ee3d1bc33030d7a91f"}, "data/2.1.2/val.zip": {"num_bytes": 506259325, "checksum": "9206de008607095bdb29f405ef9b525565556860d015cbd4261154644b51ce9b"}, "data/2.1.2/test.zip": {"num_bytes": 507619065, "checksum": "614821d8d8c92451ba495e0b381f157a0e0b36977a70f2d4cb3ae4b6b706539a"}}, "download_size": 10142923776, "post_processing_size": null, "dataset_size": 8968684827, "size_in_bytes": 19111608603}, "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": "2.1.2", "splits": {"train": {"name": "train", "num_bytes": 3695589005, "num_examples": 124397, "dataset_name": "big_patent"}, "validation": {"name": "validation", "num_bytes": 200369780, "num_examples": 6911, "dataset_name": "big_patent"}, "test": {"name": "test", "num_bytes": 204394948, "num_examples": 6911, "dataset_name": "big_patent"}}, "download_checksums": {"data/2.1.2/train.zip": {"num_bytes": 9129045386, "checksum": "59cae1439b01102faa5b9e1bb3061867ba292a6093cf66ee3d1bc33030d7a91f"}, "data/2.1.2/val.zip": {"num_bytes": 506259325, "checksum": "9206de008607095bdb29f405ef9b525565556860d015cbd4261154644b51ce9b"}, "data/2.1.2/test.zip": {"num_bytes": 507619065, "checksum": "614821d8d8c92451ba495e0b381f157a0e0b36977a70f2d4cb3ae4b6b706539a"}}, "download_size": 10142923776, "post_processing_size": null, "dataset_size": 4100353733, "size_in_bytes": 14243277509}}