PATENT CLAIM ANALYSIS

Application Number: 16200411
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2020-02
Patent Classification: ["null", "null"]

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating additional training data for a natural language understanding engine. One of the methods includes: obtaining data identifying (i) a first input conversational turn and (ii) a first annotation, determining that the first annotation accurately characterized the first input conversational turn, determining that the natural language understanding engine is likely to generate inaccurate annotations of other conversational turns that are similar to the first input conversational turn, in response to the determining, obtaining one or more first paraphrases of the first input conversational turn; and generating, for each of the one or more first paraphrases, a respective first training example that identifies the first annotation as the correct annotation for the first paraphrase; and training the natural language understanding engine on at least the first training examples.

Claim (Index 13):
One or more non-transitory computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:\n obtaining, during operation of a computer-implemented dialogue system comprising a natural language understanding engine, data identifying (i) a first input conversational turn that was provided as input to the natural language understanding engine during a dialogue between a user and the computer-implemented dialogue system and (ii) a first annotation of the first input conversational turn generated by the natural language understanding engine, wherein the natural language understanding engine has been trained on a first set of training data comprising a plurality of training conversational turns; determining that the first annotation does not accurately characterize the first input conversational turn; in response to determining that the first annotation did not accurately characterize the first input conversational turn:\n determining a correct annotation for the first conversational turn; \n obtaining one or more first paraphrases of the first input conversational turn; and \n generating, for each of the one or more first paraphrases, a respective first training example that identifies the correct annotation for the first conversational turn as the correct annotation for the first paraphrase; and \n training the natural language understanding engine on at least the first training examples.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 98.0
- Lexical Diversity: 2.23944
- Patent Class: nan
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['16051362', '15667283', '13793805', '13793854', '13793822']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5276948772867487
- 35 USC 102 Novelty (BERT): 0.6149082559497138
- Combined Prediction Score: 0.5364162151530452
- Mean Citation Score: 317.47598
- Max Citation Score: 555.0679299999998
- Similarity Product: 528.3826640591142

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

Dataset: test