PatentAP / README.md
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---
license: mit
dataset_info:
features:
- name: 'Unnamed: 0'
dtype: int64
- name: claim_input
dtype: string
- name: claim_idx
dtype: int64
- name: applicationNumber
dtype: int64
- name: applicationTypeCategory
dtype: string
- name: relatedDocumentData
dtype: float64
- name: patentClassification
dtype: string
- name: applicantCitedExaminerReferenceIndicatorCount
dtype: float64
- name: filingDate
dtype: string
- name: publicationDate
dtype: string
- name: claimNumberArrayDocument
dtype: float64
- name: abstract
dtype: string
- name: percentile
dtype: float64
- name: claim_label_101
dtype: int64
- name: claim_label_102
dtype: int64
- name: claim_label_103
dtype: int64
- name: claim_label_112
dtype: int64
- name: relatedApplicationNumber
dtype: string
- name: max_score_x
dtype: float64
- name: mean_score
dtype: float64
- name: max_citations
dtype: float64
- name: max_other_citations
dtype: float64
- name: max_article_citations
dtype: float64
- name: max_score_y
dtype: float64
- name: component
dtype: int64
- name: is_closed
dtype: int64
- name: is_open
dtype: int64
- name: is_half
dtype: int64
- name: similarity_product
dtype: float64
- name: transitional_phrase
dtype: string
- name: app_claim_id
dtype: string
- name: bert_scores_102
dtype: float64
- name: claim_label_combined
dtype: int64
- name: bert_scores_101
dtype: float64
- name: combined_pred_scores
dtype: float64
- name: claim_label_101_adjusted
dtype: int64
- name: bert_score_102_app_feats_no_hinge
dtype: float64
- name: bert_score_101_app_feats
dtype: float64
- name: bert_score_102_app_feats_w_hinge
dtype: float64
- name: bert_score_102_no_app_feats
dtype: float64
- name: dataset
dtype: string
- name: lexical_diversity
dtype: float64
- name: patent_class
dtype: float64
- name: foreignPriority
dtype: bool
splits:
- name: train
num_bytes: 2152439051
num_examples: 1485693
- name: validation
num_bytes: 402312853
num_examples: 278215
- name: test
num_bytes: 267789008
num_examples: 185477
download_size: 501745093
dataset_size: 2822540912
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
# PatentAP
<!-- Provide a quick summary of the dataset. -->
A dataset for the task of Patent Approval Prediction, which is proposed in the paper "Beyond Scaling: Predicting Patent Approval with Domain-specific
Fine-grained Claim Dependency Graph"
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed]