PATENT CLAIM ANALYSIS

Application Number: 16003794
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-10
Patent Classification: ["704", "008000"]

Abstract:
Embodiments can provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement a mixed-language question answering supplement system, the method comprising receiving a question in a target language; determining the question cannot be answered using a target-language only corpus; applying natural language processing to parse the question into at least one focus; for each focus, determining if one or more target language verbs share direct syntactic dependency with the focus; for each of the one or more verbs sharing direct syntactic dependency, determining if one or more target language entities share direct syntactic dependency with the verb; determining one or more Abstract Universal Verbal Types associated with each verb; for each of the one or more Abstract Universal Verbal Types, determining whether a dependency between a source language entity and a source language verb is of the same type as the dependency between the target language verb and the target language entity; if the dependency is similar, returning the source language entity as a member of a set; populating the set of returned source language entities for each focus in the target language question; identifying one or more parallel passages wherein all core arguments are matched; for each parallel passage: identifying the presence or absence of oblique nominal arguments; and measuring the precision of the oblique nominal arguments in the parallel passages against those present in the target language question; and returning an answer to the target question in the target language based on a scoring of the parallel passages based on the accuracy of their respective oblique nominal arguments.

Claim (Index 20):
The system as recited in  claim 19 , further configured to:\n train the cognitive system to learn the rules, wherein the training comprises determining combinations or patterns of one or more elements found in questions asked by subject matter experts working in the same knowledge domain.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 94.0
- Lexical Diversity: 2.71171
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16003772', '15297761', '15297763', '14749733', '15208134']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3517833265751408
- 35 USC 102 Novelty (BERT): 0.5432024554572419
- Combined Prediction Score: 0.3709252394633509
- Mean Citation Score: 328.050424
- Max Citation Score: 420.99826
- Similarity Product: 245.01986534158587

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

Dataset: test