Replace data URL in big_patent dataset and support streaming (#4236)

* Replace data URL in big_patent dataset

* Updata metadata JSON

* Update dummy data

* Set data URL within the same repo

* Update metadata JSON

Commit from https://github.com/huggingface/datasets/commit/a60321bf70b0f35209ec0964da90e505fc905500

big_patent.py

@@ -23,6 +23,8 @@ import os
 import datasets
 
 
+_HOMEPAGE = "https://evasharma.github.io/bigpatent/"
+
 _CITATION = """
 @misc{sharma2019bigpatent,
     title={BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization},
@@ -49,7 +51,12 @@ There are two features:
   - abstract: Patent abastract.
 """
 
-_URL = "https://drive.google.com/uc?export=download&id=1J3mucMFTWrgAYa3LuBZoLRR3CzzYD3fa"
+_REPO = "https://huggingface.co/datasets/big_patent/resolve/main/data"
+_URLS = {
+    "train": f"{_REPO}/train.zip",
+    "validation": f"{_REPO}/val.zip",
+    "test": f"{_REPO}/test.zip",
+}
 
 _DOCUMENT = "description"
 _SUMMARY = "abstract"
@@ -101,7 +108,7 @@ class BigPatent(datasets.GeneratorBasedBuilder):
         BigPatentConfig(  # pylint:disable=g-complex-comprehension
             cpc_codes=[k],
             name=k,
-            description=("Patents under Cooperative Patent Classification (CPC)" f"{k}: {v}"),
+            description=f"Patents under Cooperative Patent Classification (CPC) {k}: {v}",
         )
         for k, v in sorted(_CPC_DESCRIPTION.items())
     ]
@@ -113,38 +120,26 @@ class BigPatent(datasets.GeneratorBasedBuilder):
             description=_DESCRIPTION,
             features=datasets.Features({_DOCUMENT: datasets.Value("string"), _SUMMARY: datasets.Value("string")}),
             supervised_keys=(_DOCUMENT, _SUMMARY),
-            homepage="https://evasharma.github.io/bigpatent/",
+            homepage=_HOMEPAGE,
             citation=_CITATION,
         )
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
-        dl_path = dl_manager.download_and_extract(_URL)
-        split_types = ["train", "val", "test"]
-        extract_paths = dl_manager.extract(
-            {k: os.path.join(dl_path, "bigPatentData", k + ".tar.gz") for k in split_types}
-        )
-        extract_paths = {k: os.path.join(extract_paths[k], k) for k in split_types}
-
+        dl_paths = dl_manager.download_and_extract(_URLS)
+        split_dirs = {datasets.Split.TRAIN: "train", datasets.Split.VALIDATION: "val", datasets.Split.TEST: "test"}
         return [
             datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"path": extract_paths["train"]},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"path": extract_paths["val"]},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"path": extract_paths["test"]},
-            ),
+                name=split,
+                gen_kwargs={"path": dl_paths[split], "split_dir": split_dirs[split]},
+            )
+            for split in split_dirs
         ]
 
-    def _generate_examples(self, path=None):
+    def _generate_examples(self, path=None, split_dir=None):
         """Yields examples."""
         for cpc_code in self.config.cpc_codes:
-            filenames = glob.glob(os.path.join(path, cpc_code, "*"))
+            filenames = glob.glob(os.path.join(path, split_dir, cpc_code, "*"))
             for filename in sorted(filenames):
                 with open(filename, "rb") as fin:
                     fin = gzip.GzipFile(fileobj=fin)

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  - 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}}
+{"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. 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