PATENT CLAIM ANALYSIS

Application Number: 16005327
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-11
Patent Classification: ["707", "728000"]

Abstract:
Techniques for machine-based identification of objects extracted from text documents in natural language are disclosed. An example method may comprise: identifying matching pairs of one or more information objects corresponding to a real world object, one information object from the document and at least one information object from the document storage for a combination of global identification patterns that exist in the document and in the document storage; ascertaining consistency of the matching pairs and determining which of the one or more information objects in the document are suitable for merging into the document storage; and adding the one or more information objects from the document to the document storage to associate information objects corresponding to the real world object.

Claim (Index 4):
The method of  claim 1 , wherein adding the one or more information objects from the document to the document storage further comprises adding one or more information objects from the document to the document storage as new information objects if the one or more information objects in the document storage do not have one or more information objects in the document storage corresponding to the same real world object.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 94.0
- Lexical Diversity: 2.21053
- Patent Class: 707.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['14714556', '14663868', '15609800', '11459202', '13689659']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1719584197853208
- 35 USC 102 Novelty (BERT): 0.5356546629081002
- Combined Prediction Score: 0.2083280440975987
- Mean Citation Score: 194.494082
- Max Citation Score: 363.32578
- Similarity Product: 327.77150652936217

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

Dataset: test