Interpret-Block NLU Programming Reducing Complexity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional natural language understanding (NLU) programming is arcane and requires great expertise, with existing frameworks like Grammatical Framework and VoiceXML involving multiple layers of abstraction and special purpose programming, making it difficult to create custom applications.
Innovation Solution
The technology introduces new programming constructs and tools, including interpret-blocks and interpret-statements, which process token lists, produce scores for pattern matches, and return meanings associated with completed pattern matches, allowing for more efficient and reliable custom NLU applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional NLU programming frameworks (Grammatical Framework, VoiceXML) are used, then natural language understanding functionality is achieved, but programming complexity and expertise requirements increase significantly
Solution Approach 1:
The patent segments NLU programming into distinct, manageable components: interpret-blocks for defining patterns and meanings, interpret-statements for matching tokens against patterns, and action-statements for executing operations. This segmentation allows each component to be developed and maintained independently, reducing overall programming complexity while maintaining reliable NLU functionality.
Solution Approach 2:
The patent introduces an intermediary layer (the interpret-block and interpret-statement mechanism) that sits between raw token input and meaning interpretation. This intermediary provides a standardized interface for pattern matching and meaning assignment, shielding developers from the complexity of low-level NLU operations while ensuring reliable functionality.
2Reliability
If conventional NLU programming approaches are used, then language understanding is achieved, but development time and ease of creation decrease
Solution Approach 1:
The interpret-block structure enables self-service NLU development by providing built-in pattern matching and meaning assignment capabilities. Developers can define patterns and their associated meanings using straightforward syntax without requiring deep expertise in NLU theory or complex framework configurations, making creation easier while maintaining understanding accuracy.
Solution Approach 2:
The patent enables copying and reuse of interpret-blocks across different applications. Once a pattern and its meaning are defined in an interpret-block, they can be replicated and adapted for various NLU tasks, reducing development time and effort while maintaining consistent language understanding across applications.
3Productivity
If conventional NLU frameworks are used, then processing capability is achieved, but latency increases
Solution Approach 1:
The patent implements preliminary action by pre-compiling interpret-blocks into efficient data structures before runtime processing. Patterns and meanings are prepared in advance, allowing the interpret-statement matching process to operate quickly during actual NLU tasks, thereby reducing latency while maintaining strong processing capability.
Data Source
AI summary
A method of building a natural language understanding application is provided. The method includes receiving at least one electronic record containing programming code and creating executable code from the programming code. Further, the executable code, when executed by a processor, causes the processor to create a parse and an interpretation of a sequence of input tokens, the programming code includes an interpret-block and the interpret-block includes an interpret-statement. Additionally, the interpret-statement includes a pattern expression and the interpret-statement includes an action statement.