Datasets:
Tasks:
Summarization
Languages:
English
Multilinguality:
monolingual
Language Creators:
found
Annotations Creators:
no-annotation
Source Datasets:
original
ArXiv:
Tags:
patent-summarization
License:
| annotations_creators: | |
| - no-annotation | |
| language_creators: | |
| - found | |
| language: | |
| - en | |
| license: | |
| - cc-by-4.0 | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 100K<n<1M | |
| - 10K<n<100K | |
| - 1M<n<10M | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - summarization | |
| task_ids: [] | |
| paperswithcode_id: bigpatent | |
| pretty_name: Big Patent | |
| configs: | |
| - a | |
| - all | |
| - b | |
| - c | |
| - d | |
| - e | |
| - f | |
| - g | |
| - h | |
| - y | |
| tags: | |
| - patent-summarization | |
| dataset_info: | |
| - config_name: all | |
| features: | |
| - name: description | |
| dtype: string | |
| - name: abstract | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 23363518650 | |
| num_examples: 1207222 | |
| - name: validation | |
| num_bytes: 1290154487 | |
| num_examples: 67068 | |
| - name: test | |
| num_bytes: 1296234391 | |
| num_examples: 67072 | |
| download_size: 6447221554 | |
| dataset_size: 25949907528 | |
| - config_name: a | |
| features: | |
| - name: description | |
| dtype: string | |
| - name: abstract | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 3329778447 | |
| num_examples: 174134 | |
| - name: validation | |
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| num_examples: 9674 | |
| - name: test | |
| num_bytes: 185987552 | |
| num_examples: 9675 | |
| download_size: 6447221554 | |
| dataset_size: 3699882485 | |
| - config_name: b | |
| features: | |
| - name: description | |
| dtype: string | |
| - name: abstract | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 2574594655 | |
| num_examples: 161520 | |
| - name: validation | |
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| num_examples: 8973 | |
| - name: test | |
| num_bytes: 140741033 | |
| num_examples: 8974 | |
| download_size: 6447221554 | |
| dataset_size: 2858365068 | |
| - config_name: c | |
| features: | |
| - name: description | |
| dtype: string | |
| - name: abstract | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 2641973267 | |
| num_examples: 101042 | |
| - name: validation | |
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| num_examples: 5613 | |
| - name: test | |
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| num_examples: 5614 | |
| download_size: 6447221554 | |
| dataset_size: 2936467229 | |
| - config_name: d | |
| features: | |
| - name: description | |
| dtype: string | |
| - name: abstract | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 160467163 | |
| num_examples: 10164 | |
| - name: validation | |
| num_bytes: 8667961 | |
| num_examples: 565 | |
| - name: test | |
| num_bytes: 8713720 | |
| num_examples: 565 | |
| download_size: 6447221554 | |
| dataset_size: 177848844 | |
| - config_name: e | |
| features: | |
| - name: description | |
| dtype: string | |
| - name: abstract | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 535567259 | |
| num_examples: 34443 | |
| - name: validation | |
| num_bytes: 28549964 | |
| num_examples: 1914 | |
| - name: test | |
| num_bytes: 29843613 | |
| num_examples: 1914 | |
| download_size: 6447221554 | |
| dataset_size: 593960836 | |
| - config_name: f | |
| features: | |
| - name: description | |
| dtype: string | |
| - name: abstract | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 1297707404 | |
| num_examples: 85568 | |
| - name: validation | |
| num_bytes: 72367466 | |
| num_examples: 4754 | |
| - name: test | |
| num_bytes: 71676041 | |
| num_examples: 4754 | |
| download_size: 6447221554 | |
| dataset_size: 1441750911 | |
| - config_name: g | |
| features: | |
| - name: description | |
| dtype: string | |
| - name: abstract | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 5571186559 | |
| num_examples: 258935 | |
| - name: validation | |
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| num_examples: 14385 | |
| - name: test | |
| num_bytes: 310624265 | |
| num_examples: 14386 | |
| download_size: 6447221554 | |
| dataset_size: 6190993271 | |
| - config_name: h | |
| features: | |
| - name: description | |
| dtype: string | |
| - name: abstract | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 4988365946 | |
| num_examples: 257019 | |
| - name: validation | |
| num_bytes: 275293153 | |
| num_examples: 14279 | |
| - name: test | |
| num_bytes: 274505113 | |
| num_examples: 14279 | |
| download_size: 6447221554 | |
| dataset_size: 5538164212 | |
| - config_name: y | |
| features: | |
| - name: description | |
| dtype: string | |
| - name: abstract | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 2263877990 | |
| num_examples: 124397 | |
| - name: validation | |
| num_bytes: 123505958 | |
| num_examples: 6911 | |
| - name: test | |
| num_bytes: 125090828 | |
| num_examples: 6911 | |
| download_size: 6447221554 | |
| dataset_size: 2512474776 | |
| # Dataset Card for Big Patent | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [Big Patent](https://evasharma.github.io/bigpatent/) | |
| - **Repository:** | |
| - **Paper:** [BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization](https://arxiv.org/abs/1906.03741) | |
| - **Leaderboard:** | |
| - **Point of Contact:** [Lu Wang](mailto:wangluxy@umich.edu) | |
| ### Dataset Summary | |
| BIGPATENT, consisting of 1.3 million records of U.S. patent documents along with human written abstractive summaries. | |
| Each US patent application is filed under a Cooperative Patent Classification (CPC) code. | |
| There are nine such classification categories: | |
| - a: Human Necessities | |
| - b: Performing Operations; Transporting | |
| - c: Chemistry; Metallurgy | |
| - d: Textiles; Paper | |
| - e: Fixed Constructions | |
| - f: Mechanical Engineering; Lightning; Heating; Weapons; Blasting | |
| - g: Physics | |
| - h: Electricity | |
| - y: General tagging of new or cross-sectional technology | |
| Current defaults are 2.1.2 version (fix update to cased raw strings) and 'all' CPC codes: | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("big_patent") # default is 'all' CPC codes | |
| ds = load_dataset("big_patent", "all") # the same as above | |
| ds = load_dataset("big_patent", "a") # only 'a' CPC codes | |
| ds = load_dataset("big_patent", codes=["a", "b"]) | |
| ``` | |
| To use 1.0.0 version (lower cased tokenized words), pass both parameters `codes` and `version`: | |
| ```python | |
| ds = load_dataset("big_patent", codes="all", version="1.0.0") | |
| ds = load_dataset("big_patent", codes="a", version="1.0.0") | |
| ds = load_dataset("big_patent", codes=["a", "b"], version="1.0.0") | |
| ``` | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed] | |
| ### Languages | |
| English | |
| ## Dataset Structure | |
| ### Data Instances | |
| Each instance contains a pair of `description` and `abstract`. `description` is extracted from the Description section of the Patent while `abstract` is extracted from the Abstract section. | |
| ``` | |
| { | |
| 'description': 'FIELD OF THE INVENTION \n [0001] This invention relates to novel calcium phosphate-coated implantable medical devices and processes of making same. The unique calcium-phosphate coated implantable medical devices minimize...', | |
| 'abstract': 'This invention relates to novel calcium phosphate-coated implantable medical devices...' | |
| } | |
| ``` | |
| ### Data Fields | |
| - `description`: detailed description of patent. | |
| - `abstract`: Patent abastract. | |
| ### Data Splits | |
| | | train | validation | test | | |
| |:----|------------------:|-------------:|-------:| | |
| | all | 1207222 | 67068 | 67072 | | |
| | a | 174134 | 9674 | 9675 | | |
| | b | 161520 | 8973 | 8974 | | |
| | c | 101042 | 5613 | 5614 | | |
| | d | 10164 | 565 | 565 | | |
| | e | 34443 | 1914 | 1914 | | |
| | f | 85568 | 4754 | 4754 | | |
| | g | 258935 | 14385 | 14386 | | |
| | h | 257019 | 14279 | 14279 | | |
| | y | 124397 | 6911 | 6911 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed] | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed] | |
| #### Who are the annotators? | |
| [More Information Needed] | |
| ### Personal and Sensitive Information | |
| [More Information Needed] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed] | |
| ### Licensing Information | |
| [More Information Needed] | |
| ### Citation Information | |
| ```bibtex | |
| @article{DBLP:journals/corr/abs-1906-03741, | |
| author = {Eva Sharma and | |
| Chen Li and | |
| Lu Wang}, | |
| title = {{BIGPATENT:} {A} Large-Scale Dataset for Abstractive and Coherent | |
| Summarization}, | |
| journal = {CoRR}, | |
| volume = {abs/1906.03741}, | |
| year = {2019}, | |
| url = {http://arxiv.org/abs/1906.03741}, | |
| eprinttype = {arXiv}, | |
| eprint = {1906.03741}, | |
| timestamp = {Wed, 26 Jun 2019 07:14:58 +0200}, | |
| biburl = {https://dblp.org/rec/journals/corr/abs-1906-03741.bib}, | |
| bibsource = {dblp computer science bibliography, https://dblp.org} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@mattbui](https://github.com/mattbui) for adding this dataset. |