Understand the fundamentals of context-free grammars and their formal properties
Be able to design and construct grammar rules for natural language structures
Compare and evaluate different parsing algorithms and their computational complexity
Apply syntactic analysis techniques to real-world language data
Implement grammar induction methods to learn patterns from corpora
Generate natural language text using context-free grammar frameworks
Integrate parsing capabilities into advanced NLP applications
Activity 1: Grammar theory fundamentals
Context-free grammars (CFGs) provide a mathematical framework for describing the syntactic structure of natural languages.
Understanding their formal properties is essential for computational linguistics applications.
Interactive Grammar Explorer
Explore different types of grammar rules and their derivations:
Production Rules:
Parse Results:
Grammar Properties Analyzer
Analyze the formal properties of your grammar:
Analysis Results:
Activity 2: Interactive grammar builder
Build your own context-free grammar by defining production rules and testing them with sample sentences.
This hands-on activity helps you understand how grammar rules interact to generate language structures.
Grammar Rule Builder
Add New Rule:
Current Grammar Rules:
S → NP VP
NP → Det N
VP → V NP
Det → 'the' | 'a'
N → 'cat' | 'dog' | 'mat'
V → 'sits' | 'runs' | 'jumps'
Test Your Grammar:
Parse Result:
Grammar Validation:
Activity 3: Parsing algorithm comparison
Compare different parsing algorithms including top-down recursive descent, bottom-up shift-reduce,
and chart parsing. Understand their strengths, weaknesses, and computational complexity.
Algorithm Performance Simulator
Parsing Steps:
Performance Metrics:
Metric
Value
Algorithm Comparison:
Activity 4: Syntactic analysis laboratory
Apply syntactic analysis to real-world text data. Explore constituency parsing, dependency parsing,
and syntactic feature extraction from various text types including news articles, academic papers, and social media posts.
Text Analysis Workbench
Constituency Parsing
Parse Results:
Dependency Parsing
Dependency Structure:
Syntactic Feature Extraction
Extracted Features:
Feature
Value
Description
Cross-Genre Syntactic Analysis
Genre Comparison Results:
Activity 5: Grammar induction challenge
Learn grammar rules automatically from text corpora using computational methods. Explore different induction algorithms
and understand how machines can discover linguistic patterns without explicit programming.
Grammar Learning Laboratory
Training Corpus:
Induction Settings:
2
Learned Grammar Rules:
Rule Statistics:
Rule
Frequency
Confidence
Grammar Testing:
Activity 6: Natural language generation
Generate natural language text using context-free grammar rules. Explore different generation strategies
including random generation, template-based generation, and semantically-guided text production.
Text Generation Studio
Random Sentence Generation
3
Generated Text:
Derivation Trace:
Template-Based Generation
Generated Article:
Semantic-Guided Generation
Generated Sentences:
Semantic Analysis:
Creative Writing Assistant
Generated Story:
Grammar Patterns Used:
Style Metrics:
Activity 7: Advanced parsing applications
Integrate context-free grammar parsing into real-world NLP applications including machine translation preprocessing,
question answering systems, dialogue management, and automated essay scoring.
