PATENT CLAIM ANALYSIS

Application Number: 16073611
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2019-01
Patent Classification: ["704", "009000"]

Abstract:
A multilingual named-entity recognition system according to an embodiment includes an acquisition unit configured to acquire an annotated sample of a source language and a sample of a target language, a first generation unit configured to generate an annotated named-entity recognition model of the source language by applying Conditional Random Field sequence labeling to the annotated sample of the source language and obtaining an optimum weight for each annotated named entity of the source language, a calculation unit configured to calculate similarity between the annotated sample of the source language and the sample of the target language, and a second generation unit configured to generate a named-entity recognition model of the target language based on the annotated named-entity recognition model of the source language and the similarity.

Claim (Index 1):
A multilingual named-entity recognition system comprising:\n at least one memory operable to store program code; and at least one processor operable to read the program code and operate as instructed by the program code, the program code including: acquisition code configured to cause the at least one processor to acquire an annotated sample of a source language and a sample of a target language; first generation code configured to cause the at least one processor to generate an annotated named-entity recognition model of the source language by applying Conditional Random Field sequence labeling to the annotated sample of the source language and obtaining an optimum weight for each annotated named entity of the source language; calculation code configured to cause the at least one processor to calculate similarity between the annotated sample of the source language and the sample of the target language; and second generation code configured to cause the at least one processor to generate a named-entity recognition model of the target language based on the annotated named-entity recognition model of the source language and the similarity.

Metadata:
- Claim Count in Document: 11.0
- Percentile: 95.0
- Lexical Diversity: 2.62
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14837687', '14490275', '15512281', '12110231', '15406586']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2724789201715525
- 35 USC 102 Novelty (BERT): 0.4935004076424732
- Combined Prediction Score: 0.2945810689186446
- Mean Citation Score: 223.069488
- Max Citation Score: 243.21155
- Similarity Product: 177.90898058106004

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