big_patent / dataset_infos.json
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{"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 - summary: 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"}, "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://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa": {"num_bytes": 6448045871, "checksum": "7e1093c7e0d09677c79bd872a07b6a6dd2b3235633207e9918b75056205f04dc"}}, "download_size": 6448045871, "post_processing_size": null, "dataset_size": 25949907528, "size_in_bytes": 32397953399}, "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 - summary: 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"}, "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://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa": {"num_bytes": 6448045871, "checksum": "7e1093c7e0d09677c79bd872a07b6a6dd2b3235633207e9918b75056205f04dc"}}, "download_size": 6448045871, "post_processing_size": null, "dataset_size": 3699882485, "size_in_bytes": 10147928356}, "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 - summary: 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"}, "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://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa": {"num_bytes": 6448045871, "checksum": "7e1093c7e0d09677c79bd872a07b6a6dd2b3235633207e9918b75056205f04dc"}}, "download_size": 6448045871, "post_processing_size": null, "dataset_size": 2858365068, "size_in_bytes": 9306410939}, "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 - summary: 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"}, "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://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa": {"num_bytes": 6448045871, "checksum": "7e1093c7e0d09677c79bd872a07b6a6dd2b3235633207e9918b75056205f04dc"}}, "download_size": 6448045871, "post_processing_size": null, "dataset_size": 2936467229, "size_in_bytes": 9384513100}, "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 - summary: 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"}, "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://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa": {"num_bytes": 6448045871, "checksum": "7e1093c7e0d09677c79bd872a07b6a6dd2b3235633207e9918b75056205f04dc"}}, "download_size": 6448045871, "post_processing_size": null, "dataset_size": 177848844, "size_in_bytes": 6625894715}, "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 - summary: 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"}, "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://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa": {"num_bytes": 6448045871, "checksum": "7e1093c7e0d09677c79bd872a07b6a6dd2b3235633207e9918b75056205f04dc"}}, "download_size": 6448045871, "post_processing_size": null, "dataset_size": 593960836, "size_in_bytes": 7042006707}, "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 - summary: 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"}, "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://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa": {"num_bytes": 6448045871, "checksum": "7e1093c7e0d09677c79bd872a07b6a6dd2b3235633207e9918b75056205f04dc"}}, "download_size": 6448045871, "post_processing_size": null, "dataset_size": 1441750911, "size_in_bytes": 7889796782}, "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 - summary: 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"}, "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://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa": {"num_bytes": 6448045871, "checksum": "7e1093c7e0d09677c79bd872a07b6a6dd2b3235633207e9918b75056205f04dc"}}, "download_size": 6448045871, "post_processing_size": null, "dataset_size": 6190993271, "size_in_bytes": 12639039142}, "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 - summary: 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"}, "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://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa": {"num_bytes": 6448045871, "checksum": "7e1093c7e0d09677c79bd872a07b6a6dd2b3235633207e9918b75056205f04dc"}}, "download_size": 6448045871, "post_processing_size": null, "dataset_size": 5538164212, "size_in_bytes": 11986210083}, "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 - summary: 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"}, "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://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa": {"num_bytes": 6448045871, "checksum": "7e1093c7e0d09677c79bd872a07b6a6dd2b3235633207e9918b75056205f04dc"}}, "download_size": 6448045871, "post_processing_size": null, "dataset_size": 2512474776, "size_in_bytes": 8960520647}}