Parsing #
This page is a structured learning template. Replace the comments with clear explanations, examples, formulas, diagrams, and practical insights while keeping the Hugo shortcodes intact.
Learning Objectives #
- Explain how grammars represent sentence structure.
- Describe bottom-up chart parsing and the role of dynamic programming.
- Explain PCFG rule probabilities and probabilistic parsing.
- Discuss limitations of basic PCFGs and common improvements.
Chapter Map #
| Section | Topic | Status |
|---|---|---|
| 1 | Grammars and Sentence Structure | ☐ |
| 2 | What Makes a Good Grammar | ☐ |
| 3 | A Bottom-Up Chart Parser | ☐ |
| 4 | Probabilistic Context-Free Grammars | ☐ |
| 5 | Probabilistic CKY Parsing of PCFGs | ☐ |
| 6 | Learning PCFG Rule Probabilities | ☐ |
| 7 | Problems with PCFGs | ☐ |
| 8 | Improving PCFGs by Splitting Non-Terminals | ☐ |
| 9 | Lexicalised Context-Free Grammars | ☐ |
Big Picture #
1. Grammars and Sentence Structure ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
2. What Makes a Good Grammar ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
3. A Bottom-Up Chart Parser ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
4. Probabilistic Context-Free Grammars ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
5. Probabilistic CKY Parsing of PCFGs ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
6. Learning PCFG Rule Probabilities ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
7. Problems with PCFGs ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
8. Improving PCFGs by Splitting Non-Terminals ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
9. Lexicalised Context-Free Grammars ☆ #
Definition #
Intuition #
Key Concepts #
Formula or Model #
Worked Example #
Why It Matters in NLP #
Key Points to Remember #
Practical Exploration #
Parse example sentences using a context-free grammar and inspect alternative parse trees.
# Add a minimal, well-commented Python example here.
Comparison Table #
| Concept or Model | Main Idea | Strength | Limitation | Typical Use |
|---|---|---|---|---|
Common Mistakes #
Practice Questions #
Key Takeaways #
Understanding Checklist #
- I can explain Grammars and Sentence Structure without referring to notes.
- I can explain What Makes a Good Grammar without referring to notes.
- I can explain A Bottom-Up Chart Parser without referring to notes.
- I can explain Probabilistic Context-Free Grammars without referring to notes.
- I can explain Probabilistic CKY Parsing of PCFGs without referring to notes.
- I can explain Learning PCFG Rule Probabilities without referring to notes.
- I can explain Problems with PCFGs without referring to notes.
- I can explain Improving PCFGs by Splitting Non-Terminals without referring to notes.
- I can explain Lexicalised Context-Free Grammars without referring to notes.