NLP Support

This section documents the Natural Language Processing (NLP) services and capabilities that the NDF Studio system depends on.

Overview

The NDF Studio system uses NLP services for:

• Parsing CNL (Controlled Natural Language) input
• Extracting structured data from natural language
• Text analysis and processing
• Language understanding and interpretation

External Dependencies

NLP Libraries and Services

• spaCy: Advanced natural language processing
• NLTK: Natural language toolkit for text processing
• TextBlob: Simple text processing and sentiment analysis
• Custom CNL Parser: Domain-specific language parsing

Core NLP Functions

• Text Tokenization: Breaking text into meaningful units
• Part-of-Speech Tagging: Identifying grammatical components
• Named Entity Recognition: Extracting entities from text
• Dependency Parsing: Understanding sentence structure
• Semantic Analysis: Understanding meaning and context

Integration Points

CNL Processing Pipeline

1. Input Validation: Checking CNL syntax and structure
2. Tokenization: Breaking CNL into parseable units
3. Entity Extraction: Identifying nodes, relations, and attributes
4. Structure Building: Creating graph structures from parsed text
5. Validation: Ensuring extracted structures are valid

Text Analysis Features

• Sentiment Analysis: Understanding emotional context
• Keyword Extraction: Identifying important terms
• Text Classification: Categorizing content
• Summarization: Creating concise representations

Configuration

NLP services are configured through: - Language model selection - Processing pipeline configuration - Performance optimization settings - Custom domain-specific rules