README.md

metadata

annotations_creators:
  - no-annotation
language_creators:
  - found
languages:
  - en
licenses:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - n>1M
source_datasets:
  - original
task_categories:
  - conditional-text-generation
task_ids:
  - summarization

Dataset Card for Big Patent

Table of Contents

• Dataset Card for Big Patent
  • Table of Contents
  • Dataset Description
    • Dataset Summary
    • Supported Tasks and Leaderboards
    • Languages
  • Dataset Structure
    • Data Instances
    • Data Fields
    • Data Splits
  • Dataset Creation
    • Curation Rationale
    • Source Data
      • Initial Data Collection and Normalization
      • Who are the source language producers?
    • Annotations
      • Annotation process
      • Who are the annotators?
    • Personal and Sensitive Information
  • Considerations for Using the Data
    • Social Impact of Dataset
    • Discussion of Biases
    • Other Known Limitations
  • Additional Information
    • Dataset Curators
    • Licensing Information
    • Citation Information

Dataset Description

• Homepage:Big Patent
• Repository:
• Paper:BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization
• Leaderboard:
• Point of Contact:

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)

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.

Data Fields

• description: detailed description of patent.
• abstract: Patent abastract.

Data Splits

[More Information Needed]

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

[More Information Needed]