Datasets:

Trelis
/

big_patent_100k_characters

description stringlengths 4.57k 100k	abstract stringlengths 89 2.31k	description_length int64 4.57k 100k
FIELD OF THE INVENTION The present invention relates to systems and methods for monitoring service on communications networks, and particularly to systems and methods that cause minimal disruption to the communications network traffic by using passive monitoring of network traffic data packets. BACKGROUND O...	A system and method for determining optimal selection of paths for passively monitoring a communications network. A diagnostic set of paths is determined by ensuring that, for all pairs of links in the network, the set contains one path having only one member of that pair. A detection subset of paths is determined by e...	28,063
CROSS REFERENCES TO RELATED APPLICATIONS This application claims priority from and is related to commonly owned U.S. Provisional Patent Application Ser. No. 61/452,450 filed Mar. 14, 2011, entitled: Apparatus for Plasma Dicing a Semi-conductor Wafer, this Provisional Patent Application incorporated by reference h...	The present invention provides a method for plasma dicing a substrate, the method comprising providing a process chamber having a wall; providing a plasma source adjacent to the wall of the process chamber; providing a work piece support within the process chamber; placing a work piece onto the work piece support, said...	65,247
BACKGROUND INFORMATION [0001] 1. Field [0002] Embodiments of the disclosure relate generally to the field of packaging for pastry and baked goods and more particularly to a multidiametric case for a cupcake or similar good, the case having a relieved upper portion for clearance of frosting or to...	A cupcake package includes a base element having a primary diameter for receiving a cupcake body and a relieving cylinder having a second diameter extending from the base element for clearance of a top contour of the cupcake. A bottom surface closes the base element and includes an aperture centrally located therein si...	11,558
BACKGROUND OF THE INVENTION [0001] 1. Field of the Invention [0002] The present invention relates to ecology, and more specifically to a System and method for saving the rainforests. [0003] 2. Background [0004] The destruction of the rainforests in the last ...	The destruction of the rainforests in the last decades has become the biggest crime against humanity, animals and Nature. Various statistics show that at the current rate of destruction, unless drastic changes are made right now, by the year 2020 or even considerably earlier, 90-100% of all the rainforests will be irre...	65,543
BACKGROUND OF THE INVENTION [0001] 1. Field of the Invention [0002] The present invention relates to magnetic separation generally and, more particularly, but not by way of limitation, to a novel apparatus that permits the automatic separation of magnetic components in a laboratory micropl...	In a preferred embodiment, an apparatus for automated magnetic separation of materials in laboratory trays, including: a frame upon an upper surface of which a multiwell laboratory tray may be placed; a base plate on which is mounted a plurality of upstanding magnets disposed below the upper surface; and apparatus to r...	13,464
"BACKGROUND \n [0001] A common environment scenario is mixed-mode, wherein differing versio(...TRUNCATED)	"Versioning management provides for efficient and effective handling of varying policy versions, cli(...TRUNCATED)	95,596
"TECHNICAL FIELD \n [0001] The invention relates to a broadcast communication system archit(...TRUNCATED)	"This invention discloses a digital TV broadcast system coordinated with a broadband communication n(...TRUNCATED)	50,572
"BACKGROUND OF THE INVENTION \n 1. Field of the Invention \n The present invention relates t(...TRUNCATED)	"The present invention provides novel carbonic anhyrase inhibitors represented by the structural for(...TRUNCATED)	53,613
"This is a division, of application Ser. No. 749,589, filed June 27, 1985, now abandoned. \n \n (...TRUNCATED)	"An integrated circuit in complementary circuit technology comprising two field effect transistors ((...TRUNCATED)	16,046
"[0001] This application is a divisional of application Ser. No. 10/226,190, filed on Aug. 23, 20(...TRUNCATED)	"An image sensor includes a pixel having a protection circuit connected to a charge multiplying phot(...TRUNCATED)	27,186

End of preview. Expand in Data Studio

Sampled Big Patent Dataset

This is a sampled Trelis/big_patent_sample dataset containing rows of data with descriptions shorter than or equal to 100,000 characters in length.

--- Sampled from Trelis/big_patent_sampled ---

Sampled big_patent Dataset

This is a sampled big_patent dataset - sampled down for shorter fine-tunings.

The data is sampled with the aim of providing an even distribution across data lengths. The distribution is quite flat up until 1 million characters in length, making the dataset good for training on lengths up to 250,000 tokens.

Dataset Card for Big Patent

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:

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:

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

@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}
}