PATENT CLAIM ANALYSIS

Application Number: 16181102
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-10
Patent Classification: ["704", "009000"]

Abstract:
Methods are presented for generating a natural language model. The method may comprise: ingesting training data representative of documents to be analyzed by the natural language model, generating a hierarchical data structure comprising at least two topical nodes within which the training data is to be subdivided into by the natural language model, selecting a plurality of documents among the training data to be annotated, generating an annotation prompt for each document configured to elicit an annotation about said document indicating which node among the at least two topical nodes said document is to be classified into, receiving the annotation based on the annotation prompt; and generating the natural language model using an adaptive machine learning process configured to determine patterns among the annotations for how the documents in the training data are to be subdivided according to the at least two topical nodes of the hierarchical data structure.

Claim (Index 10):
The method of  claim 1 , wherein generating the hierarchical data structure comprises:\n generating, by the natural language platform, at least one annotation prompt for each topical node among the two or more topical nodes in the hierarchical data structure, said annotation prompt configured to elicit an annotation about said topical node indicating a level of accuracy of placement of the node within the hierarchical data structure; causing display of, by the natural language platform, the at least one annotation prompt for each topical node; and receiving, by the natural language platform, for each topical node, the annotation in response to the displayed annotation prompt.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 2.18056
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14964517', '14964512', '14964511', '14964526', '14143011']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3023899081552221
- 35 USC 102 Novelty (BERT): 0.6190401898540578
- Combined Prediction Score: 0.3340549363251056
- Mean Citation Score: 323.3262519999999
- Max Citation Score: 558.064
- Similarity Product: 536.0452541532517

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test