PATENT CLAIM ANALYSIS

Application Number: 15893343
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-06
Patent Classification: ["704", "002000"]

Abstract:
A machine or computer rule-based based translation system and method which translates texts (conveying their meanings) from one natural language to another. The system and method have a modular structure for organizing languages, which in combination with a transitory (indirect) method of translation allows for the creation of a multilingual system that is capable of translations in any direction between any of the included languages. Every linguistic module includes a dictionary of words and phrases, a list of operational functions, and parameters that guide the conversion processes needed to perform a translation from one language to another.

Claim (Index 7):
A method for translation of a source text conveying its meaning from one natural language to another natural language and into a translated text, comprising\n entering said source text to be translated into a field of a GUI for entering said source text to a core of a computer configured for translation of said source text;\n initiating a translation process; \n separating said source text into tokens; \n identifying lexemes from the tokenization step; \n assigning attributes to said lexemes; \n analyzing said lexemes; \n eliminating ambiguities of said lexemes; \n establishing dependencies between words; \n applying translation grammar and synthesis grammar to the translated text in order to determine if in the translated text there are: lexemes; attributes assigned to each token; and dependencies between tokens; \n applying rules of synthesis to correct any excess or deficiency of the attributes in said translated text and any excess or absence of dependencies in said translated text, and correcting any word order in the translated text; \n analyzing source and target texts thereby establishing matches resulting in self-learning automatically filling the dictionaries with new phrases for self-learning; wherein a token is an element that represents a sequence of symbols grouped by predefined characteristics, such as an identifier, a number, a punctuation mark, date, or word, each token within a source text being separated by a space, so that all elements located between spaces are identified as separate tokens, wherein said grammar is a functional block that transforms linguistic information and includes of a list of rules, which are performed consecutively, wherein grammar rules, comprise a sequence of operators, wherein grammars work with incoming linguistic information, divided into tokens with defined initial attributes that are obtained from an orthographical dictionary, wherein grammar has input parameters, through which information is received, wherein real values of parameters are provided to grammar input, wherein said values are stored in a current list, said current list being an internal buffer for storing results of intermediate modifications, and conveying said translated text to an output for display.

Metadata:
- Claim Count in Document: 9.0
- Percentile: 88.0
- Lexical Diversity: 1.57353
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['11784449', '12692667', '15247490', '10571760', '12446232']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2581049607302712
- 35 USC 102 Novelty (BERT): 0.5172819011477424
- Combined Prediction Score: 0.2840226547720183
- Mean Citation Score: 274.44827200000003
- Max Citation Score: 305.6618
- Similarity Product: 228.6872859696627

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

Dataset: test