Natural Language Processing

By

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S.V.V.D.Jagadeesh

Sr. Assistant Professor

Dept of Artificial Intelligence & Data Science

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LAKIREDDY BALI REDDY COLLEGE OF ENGINEERING

• Previously Discussed Topics
• Session Outcomes
• Syntax- Driven Semantic Analyis
• Principle of Compositionability
• Semantic Augmentation to CFG Rules
• Quantifier Scope Ambiguity
• Unification Based Approaches
• Semantic Attachments
• Sentences

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Previously Discussed Topics

LBRCE

NLP

• Noun and Genitive Noun Phrases
• Adjective Phrases
• Verb Phrases
• Infinite Verb Phrases
• Prepositional Phrases
• Nominal modifier Prepositional Phrases
• Verb Phrase Prepositional Phrases
• Verb Argument Prepositional Phrases
• Idioms and Compositionability
• Challenges with Idioms

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Previously Discussed Topics

LBRCE

NLP

At the end of this session, Student will be able to:

• Understand Word Senses and their Relationships(Understand-L2)

S.V.V.D.Jagadeesh

Friday, March 13, 2026

Session Outcomes

LBRCE

NLP

• Lexical semantics is the branch of linguistics and NLP that studies the meaning of words and the relationships between word meanings.
• In natural language processing, understanding the meaning of words is essential for tasks such as:
• Machine translation
• Information retrieval
• Question answering
• Text summarization
• Word sense disambiguation

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Lexical Semantics

LBRCE

NLP

• A word sense is one of the possible meanings of a word.
• Many words are ambiguous because they have multiple senses.
• Example Word: bank
• Possible meanings: Financial institution, Edge of a river
• Example Sentences
• Sentence 1: She deposited money in the bank.
• Meaning: bank = financial institution
• Sentence 2: They sat on the bank of the river.
• Meaning: bank = river edge
• Thus, the correct sense depends on the context.

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Word Sense

LBRCE

NLP

• Polysemy
• Homonymy
• Homophones
• Homographs
• Metonymy

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Types of Word Senses

LBRCE

NLP

• Polysemy occurs when a word has multiple related meanings.
• The meanings share a common semantic origin.
• Example Word: paper
• Possible meanings: Writing material, Academic article, Newspaper
• Example Sentences
• She wrote her notes on paper.
• He published a research paper.
• I read the morning paper.
• All senses relate to written information.

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Polysemy

LBRCE

NLP

• Homonymy occurs when two words share the same spelling or pronunciation but have unrelated meanings.
• Example Word: bat
• Meaning 1: flying mammal
• Meaning 2: sports equipment
• Example Sentences
• The bat flew out of the cave.
• He hit the ball with the bat.

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Homonymy

LBRCE

NLP

• Homophones are words that sound the same but have different meanings and spellings.
• Example
• flower – flour
• Examples
• She bought a flower.
• The cake needs flour.

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Homophones

LBRCE

NLP

• Homographs are words that have the same spelling but different meanings and sometimes different pronunciations.
• Example
• lead
• Meaning 1: metal
• Meaning 2: to guide
• Examples
• The pipes are made of lead.
• She will lead the team.

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Homographs

LBRCE

NLP

• Metonymy occurs when a word is used to refer to something closely associated with it, rather than the thing itself.
• In metonymy, one entity stands for another related entity.
• Example
• Sentence: The White House announced new policies.
• Meaning: White House → U.S. government administration
• Example
• Hollywood produces many movies.
• Meaning: Hollywood → American film industry
• Metonymy is common in everyday language and must be handled by NLP systems.

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Metonymy

LBRCE

NLP

• Lexical semantics studies relationships between meanings of words.
• These relationships help organize vocabulary in semantic networks.
• Types of Relationships:
• Synonomy
• Antonymy
• Hypernymy
• Hyponymy
• Meronymy
• Holonymy
• Semantic Fields

S.V.V.D.Jagadeesh

Friday, March 13, 2026

Relationships Between Word Senses

LBRCE

NLP

S.V.V.D.Jagadeesh

Friday, March 13, 2026

Synonymy

• Synonyms are words with similar meanings
• Examples
• big – large�car – automobile
• Example sentences
• This is a big building.
• This is a large building.

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LBRCE

NLP

• Antonyms are words with opposite meanings.
• Examples
• hot – cold�happy – sad
• Example
• The coffee is hot.
• The ice cream is cold.

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Antonymy

LBRCE

NLP

• A hypernym is a more general term representing a category.
• Example
• animal → dog
• Meaning
• A dog is a type of animal.

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Hypernymy (Is-A Relationship)

LBRCE

NLP

• A hyponym is a more specific word within a category.
• Example
• dog → animal
• Example hierarchy
• vehicle� ├── car� ├── bus� └── truck

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Hyponymy

LBRCE

NLP

• Meronymy represents a part-of relationship
• Examples
• wheel → car�finger → hand�page → book�engine → car
• Example sentence
• A wheel is part of a car.

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Meronymy (Part-Whole Relationship)

LBRCE

NLP

• Holonymy represents the whole-to-part relationship.
• Example
• car → wheel
• Meaning
• A car has wheels.

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Holonymy

LBRCE

NLP

S.V.V.D.Jagadeesh

Friday, March 13, 2026

Semantic Fields

• A semantic field is a group of words that are related in meaning and belong to the same conceptual domain.
• Words within a semantic field share a common conceptual area.
• Example: Color Field
• red�blue�green�yellow
• All belong to the color semantic field.

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LBRCE

NLP

S.V.V.D.Jagadeesh

Friday, March 13, 2026

Semantic Fields

• Example: Transportation Field
• car�bus�train�airplane�bicycle
• All belong to the transportation semantic field.

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LBRCE

NLP

S.V.V.D.Jagadeesh

Friday, March 13, 2026

Semantic Fields

• Example: Emotion Field
• happy�sad�angry�excited�afraid
• These words describe emotions.
• Semantic fields help NLP systems organize vocabulary into meaningful conceptual groups.

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LBRCE

NLP

• Previously Discussed Topics
• Session Outcomes
• Lexical Semantics
• Word Sense
• Types of word Senses
• Polysemy
• Polynymy
• Homophones
• Homographs

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Summary

LBRCE

NLP

• Metonymy
• Relationship between Word Senses
• Synonymy
• Antonymy
• Hypernymy (Is-A Relationship)
• Hyponymy
• Meronymy (part-Whole Relationship)
• Holonymy
• Semantic Fields

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S.V.V.D.Jagadeesh

Friday, March 13, 2026

Summary

LBRCE

NLP