# Q3A · Ambiguity and bottom-up parsing

Subject: Natural Language Processing

Exam: TEE

Reader: https://deep-learning-study-room.vercel.app/nlp/#tee/mocks/timed-final-2025/final-2025-q3a

Canonical: https://deep-learning-study-room.vercel.app/read/nlp/tee/mocks/timed-final-2025--final-2025-q3a/

TEE · actual previous paper · 100 marks · 180 minutes

Question. i. Explain the various types of ambiguities encountered in Natural Language Processing (NLP). Illustrate each type with suitable examples.  
ii. Compare top-down and bottom-up parsing and apply bottom-up syntax parsing approach to the sentence “A cat chased the mouse” and draw a parse tree using the grammar rules:  
S → NP VP; NP → Pronoun | Proper-Noun | Det Nominal; Nominal → Noun | Nominal Noun | Nominal PP; VP → Verb | Verb NP | VP PP; PP → Prep NP.  
Lexicon: Det → {A, the}; Noun → {cat, mouse}; Verb → {chased}. [10 marks]

### Answer

### i. Types of ambiguity

Ambiguity exists when the same language expression permits more than one interpretation. The correct interpretation usually requires grammatical, semantic or contextual evidence.

| Type | Meaning | Example and readings |
| --- | --- | --- |
| Lexical | One word has multiple meanings | “She visited the bank”: financial institution or riverbank |
| Syntactic | The sentence permits different structural attachments | “I saw the man with a telescope”: I used the telescope, or the man had it |
| Semantic / scope | A structured sentence permits different interpretations | “Every student read a book”: one shared book, or possibly a different book per student |
| Referential | A referring expression has more than one candidate referent | “Asha told Riya that she won”: she could refer to Asha or Riya |
| Pragmatic | Intention depends on the situation | “Can you open the door?” can ask about ability or request an action |

### ii. Parsing approaches

| Aspect | Top-down | Bottom-up |
| --- | --- | --- |
| Start | The start symbol S | The input words |
| Operation | Expand a nonterminal using grammar productions | Combine words and constituents using productions in reverse |
| Success | Leaves match the complete input | All input is reduced to S |
| Possible difficulty | Naive recursive descent can loop on left recursion or need backtracking | A naive shift-reduce parser may face shift/reduce conflicts |

### Given

The five tokens are A / cat / chased / the / mouse. The supplied grammar permits determiner + nominal noun phrases and a verb + noun phrase verb phrase.

### To find

A bottom-up sequence of reductions and a parse tree whose root is S and whose leaves preserve the input order.

### Rule: which one and why

A production A → B C permits B C to be reduced to A. Bottom-up parsing begins with the words; lexical rules assign their categories, and phrase rules combine those categories.

### Step 1. Assign lexical categories

A → Det; cat → Noun; chased → Verb; the → Det; mouse → Noun.

### Step 2. Build the first noun phrase

cat is Noun. Reduce Noun to Nominal using Nominal → Noun. Then reduce Det Nominal, representing “A cat”, to NP.

### Step 3. Build the object noun phrase

mouse is Noun. Reduce it to Nominal. Reduce “the” + “mouse”, now Det Nominal, to NP.

### Step 4. Build the verb phrase

“chased” is Verb and “the mouse” is NP. Reduce Verb NP to VP.

### Step 5. Build the sentence

The remaining constituents are NP (“A cat”) and VP (“chased the mouse”). Apply S → NP VP in reverse to obtain S. Every input token is used exactly once.

SNPVPDetNominalVerbNPNounDetNominalNounAcatchasedthemouse

Bottom-up parse tree for A cat chased the mouse.

**Final answer:** [S [NP [Det A] [Nominal [Noun cat]]] [VP [Verb chased] [NP [Det the] [Nominal [Noun mouse]]]]].

**Yaad rakho:** Bottom-up: words se phrases, phrases se S. Top-down: S se words.