|
--- |
|
annotations_creators: |
|
- no-annotation |
|
language_creators: |
|
- found |
|
languages: |
|
- en |
|
licenses: |
|
- unknown |
|
multilinguality: |
|
- monolingual |
|
size_categories: |
|
a: |
|
- 100K<n<1M |
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all: |
|
- 1M<n<10M |
|
b: |
|
- 100K<n<1M |
|
c: |
|
- 100K<n<1M |
|
d: |
|
- 10K<n<100K |
|
e: |
|
- 10K<n<100K |
|
f: |
|
- 10K<n<100K |
|
g: |
|
- 100K<n<1M |
|
h: |
|
- 100K<n<1M |
|
y: |
|
- 100K<n<1M |
|
source_datasets: |
|
- original |
|
task_categories: |
|
- summarization |
|
task_ids: |
|
- summarization-other-patent-summarization |
|
paperswithcode_id: bigpatent |
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pretty_name: Big Patent |
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--- |
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|
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# Dataset Card for Big Patent |
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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## Dataset Description |
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- **Homepage:** [Big Patent](https://evasharma.github.io/bigpatent/) |
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- **Repository:** |
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- **Paper:** [BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization](https://arxiv.org/abs/1906.03741) |
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- **Leaderboard:** |
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- **Point of Contact:** |
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|
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### Dataset Summary |
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|
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: |
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|
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- A (Human Necessities) |
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- B (Performing Operations; Transporting) |
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- C (Chemistry; Metallurgy) |
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- D (Textiles; Paper) |
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- E (Fixed Constructions) |
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- F (Mechanical Engineering; Lightning; Heating; Weapons; Blasting) |
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- G (Physics) |
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- H (Electricity) |
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- Y (General tagging of new or cross-sectional technology) |
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### Supported Tasks and Leaderboards |
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[More Information Needed] |
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### Languages |
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English |
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## Dataset Structure |
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### Data Instances |
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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. |
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### Data Fields |
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|
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- `description`: detailed description of patent. |
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- `abstract`: Patent abastract. |
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### Data Splits |
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|
|
| | train | validation | test | |
|
|:----|------------------:|-------------:|-------:| |
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| all | 1207222 | 67068 | 67072 | |
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| a | 174134 | 9674 | 9675 | |
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| b | 161520 | 8973 | 8974 | |
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| c | 101042 | 5613 | 5614 | |
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| d | 10164 | 565 | 565 | |
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| e | 34443 | 1914 | 1914 | |
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| f | 85568 | 4754 | 4754 | |
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| g | 258935 | 14385 | 14386 | |
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| h | 257019 | 14279 | 14279 | |
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| y | 124397 | 6911 | 6911 | |
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|
|
## Dataset Creation |
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|
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### Curation Rationale |
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|
[More Information Needed] |
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### Source Data |
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#### Initial Data Collection and Normalization |
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[More Information Needed] |
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#### Who are the source language producers? |
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[More Information Needed] |
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### Annotations |
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#### Annotation process |
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[More Information Needed] |
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#### Who are the annotators? |
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[More Information Needed] |
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### Personal and Sensitive Information |
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|
|
[More Information Needed] |
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## Considerations for Using the Data |
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|
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### Social Impact of Dataset |
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|
|
[More Information Needed] |
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### Discussion of Biases |
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|
|
[More Information Needed] |
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|
|
### Other Known Limitations |
|
|
|
[More Information Needed] |
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|
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## Additional Information |
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|
|
### Dataset Curators |
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|
|
[More Information Needed] |
|
|
|
### Licensing Information |
|
|
|
[More Information Needed] |
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|
### Citation Information |
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|
|
```bibtex |
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@article{DBLP:journals/corr/abs-1906-03741, |
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author = {Eva Sharma and |
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Chen Li and |
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Lu Wang}, |
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title = {{BIGPATENT:} {A} Large-Scale Dataset for Abstractive and Coherent |
|
Summarization}, |
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journal = {CoRR}, |
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volume = {abs/1906.03741}, |
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year = {2019}, |
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url = {http://arxiv.org/abs/1906.03741}, |
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eprinttype = {arXiv}, |
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eprint = {1906.03741}, |
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timestamp = {Wed, 26 Jun 2019 07:14:58 +0200}, |
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biburl = {https://dblp.org/rec/journals/corr/abs-1906-03741.bib}, |
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bibsource = {dblp computer science bibliography, https://dblp.org} |
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} |
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``` |
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|
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### Contributions |
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|
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Thanks to [@mattbui](https://github.com/mattbui) for adding this dataset. |
