SlideShare uma empresa Scribd logo
1 de 4
Six Sentence Patterns
Sentence Patterns #1 - Noun / Verb
The most basic sentence pattern is a noun followed by a verb. It's important to remember that only verbs that do not
require objects are used in this sentence pattern.
Examples:
People work.
Frank eats.
This basic sentence pattern can be modified by adding a noun phrase, possessive adjective, as well as other elements. This
is true for all the sentence patterns that follow.
Examples:
People work. -> Our employees work.
Frank eats. -> My dog Frank eats.
Sentence Patterns #2 - Noun / Verb / Noun
The next sentence pattern builds on the first pattern and is used with nouns that can take objects.
Examples:
John plays softball.
The boys are watching TV.
Sentence Patterns #3 - Noun / Verb / Adverb
The next sentence pattern builds on the first pattern by using an adverb to describe how an action is done.
Examples:
Thomas drives quickly.
Anna doesn't sleep deeply.
Sentence Patterns #4 - Noun / Linking Verb / Noun
This sentence pattern uses linking verbs to link one noun to another. Linking verbs are also known as equating verbs -
verbs which equate one thing with another such as 'be', 'become', 'seem', etc.
Examples:
Jack is a student.
This seed will become an apple.
Sentence Patterns #5 - Noun / Linking Verb / Adjective
This sentence pattern is similar to sentence pattern #4, but uses linking verbs to link one noun to its description using an
adjective.
Examples:
My computer is slow!
Her parents seem unhappy.
Sentence Patterns #6 - Noun / Verb / Noun / Noun
Sentence pattern #6 is used with verbs that take both direct and indirect objects.
Examples:
I bought Katherine a gift.
Jennifer showed Peter her car.
SENTENCE PATTERN DEFINITION
-Sentence pattern refers to the grammatical structure of English that describe how the nature of speech should be. This
denotes how, when and where the use of prefixes is applicable. With the use of these patterns you will be able to
recognize the necessity of punctuation in English.
There are five important components in a sentence.
e.g.
Subject (S) Verb (V) Object (O)
Complement (C) Adverbial (A)
1. SUBJECT (S)
Definition :
To get ‘S’ ask the quesiton ‘Who?’ before the verb.
e.g.
Nancy danced well (Here “Nancy” - Subject)
The child broke the glass (Here “The child” - Subject)
Subject (S)
consists of nouns or pronouns
occurs before a verb
2. VERB (V)
Definition :
In every sentence the most important word is the verb. A verb shows action or activity or work done.
e.g.
He is a doctor (“Be” form verb)
Jems wrote a letter (Main verb)
The baby is crying (auxiliary verb + Main verb)
Verb (V)
consists of (a) auxiliaries
(b) finite verbs
(a) Auxiliaries
e.g.
am, is, are ,was, were
has, have, had
does, do, did
Modals : can, could; will, would; shall, should; may, might; must
Semi-modals / Quasi Modals : dare to; need to; used to; ought to
(b) Finte verbs - denote action
e.g.
talk, sing, write, make, dance, play, cook, leave, teach, sleep
- verbs occur after the subject
- vebs occur before the object
3. OBJECT (O)
Definition :
To get the object ‘O’ ask the question ‘What’ or ‘Whome’. ‘What’ is for things and ‘Whome’ is for persons. Persons may
be nouns or pronouns.
e.g.
He bought a pen (a pen = Object)
He handles the computer (computer = Object)
I saw him (him = Object)
Object (O) - consists of nouns or noun phrases or noun clauses
(a) Do
- direct object
- answers the question ‘what’
e.g.
S V O (what)
I likes animals
(b) IO
- indirect object
- answers the question ‘whom’
e.g.
S V IO (whom) DO
I gave Rosy a pen
4. COMPLEMENT (C)
Definition :
The words required to complete the meaning of a sentence are called Complement of the sentence.
e.g.
S V C
He is a dentist
She became a journalist
It grew dark
Complement (C) - from the word ‘complete’
- completes the meaning in the sentence
- wihtout it the, meaning is incomplete
- wihtout it the, meaning changes
occurs in two pattern. (i) S V C pattern. (ii) S V O C pattern
(i) In S V C pattern, the complement C
- complements the subjects
- tells about the subject
- wihtout it the, meaning changes
- without C, the sentence is incomplete or the sentence changes its meaning
- use to be forms, grew, became, seems for verb
e.g.
S V C
They are players
She was angry
It seems absurd
(ii) In S V O C pattern
- the complement tells about the object
- the complement and object are of the same person or thing
e.g.
S V O C
They called David a genius
I found her crying
They elected Michle leader
Types of Complement
1. Subject Complement
Definition :
The complement which expresses the quality or identity or condition of the subject is called Subject Complement.
e.g.
She is a doctor She looks sad
2. Object Complement
Definition :
The complement which expresses the quality or identity or condition of an object is called Object Complement.
e.g.
They made her angry She called him a liar
Adjunct or Adverbial
Definition :
To get ‘A’ ask the question why, when, where or how.
The use of adverbial is optional whereas complement is essential. It has adverb phrase, adverbial clause, noun-phrase and
prepositional phrase.
e.g.
Why? (reason) When? (Time) Where? (Place) How? (Manner)
due to cold now, later here, there by bus / cycle
through floods after 2 years every where through efforts
under compulsion when young in the sky by mixing
carefully in the morning at home by hard work
Adjunct - A - answers the questions where? when? how? why?
- without A, any change in the meaning of the sentence
Examples of Adjuncts in sentences
e.g.
S V A
She Comes every day
- Sit here

Mais conteúdo relacionado

Mais procurados (20)

Sentence patterns
Sentence patternsSentence patterns
Sentence patterns
 
Complements
ComplementsComplements
Complements
 
Direct and Indirect Object Pronouns
Direct and Indirect Object PronounsDirect and Indirect Object Pronouns
Direct and Indirect Object Pronouns
 
Ppt noun clause
Ppt noun clausePpt noun clause
Ppt noun clause
 
direct object pronouns
direct object pronounsdirect object pronouns
direct object pronouns
 
Unit 13 arguments of the verb, subject, object and indirect object
Unit 13   arguments of the verb, subject, object and indirect objectUnit 13   arguments of the verb, subject, object and indirect object
Unit 13 arguments of the verb, subject, object and indirect object
 
How to analyse sentences
How to analyse sentencesHow to analyse sentences
How to analyse sentences
 
Sentence elements
Sentence elementsSentence elements
Sentence elements
 
Eng. copy
Eng. copyEng. copy
Eng. copy
 
Passive voice 00 final ppt long class (2 hours)
Passive voice 00 final ppt long class (2 hours)Passive voice 00 final ppt long class (2 hours)
Passive voice 00 final ppt long class (2 hours)
 
Pronoun by tanbircox
Pronoun by tanbircoxPronoun by tanbircox
Pronoun by tanbircox
 
EN102 (Communication Arts 2)
EN102 (Communication Arts 2)EN102 (Communication Arts 2)
EN102 (Communication Arts 2)
 
Active and Passive Voice
Active and Passive VoiceActive and Passive Voice
Active and Passive Voice
 
GRAMMAR EXPLANATION
GRAMMAR EXPLANATIONGRAMMAR EXPLANATION
GRAMMAR EXPLANATION
 
Types of clauses
Types of clausesTypes of clauses
Types of clauses
 
The verb
The verbThe verb
The verb
 
Sentence Structure
Sentence StructureSentence Structure
Sentence Structure
 
Noun clause functions
Noun clause functionsNoun clause functions
Noun clause functions
 
Ingles pronombres 30 diapositivas
Ingles pronombres 30 diapositivasIngles pronombres 30 diapositivas
Ingles pronombres 30 diapositivas
 
Noun Clauses
Noun ClausesNoun Clauses
Noun Clauses
 

Semelhante a Cce

Semelhante a Cce (20)

Cce
CceCce
Cce
 
Verbs 1
Verbs 1Verbs 1
Verbs 1
 
Complements 8
Complements 8Complements 8
Complements 8
 
Sentences.pptx
Sentences.pptxSentences.pptx
Sentences.pptx
 
CASES-of-PRONOUN.pptx
CASES-of-PRONOUN.pptxCASES-of-PRONOUN.pptx
CASES-of-PRONOUN.pptx
 
Nouns.verbs.tenses
Nouns.verbs.tensesNouns.verbs.tenses
Nouns.verbs.tenses
 
Eight Parts of Speech.pdf
Eight Parts of Speech.pdfEight Parts of Speech.pdf
Eight Parts of Speech.pdf
 
Eight-Parts-of-Speech.pptx
Eight-Parts-of-Speech.pptxEight-Parts-of-Speech.pptx
Eight-Parts-of-Speech.pptx
 
Basic Sentence Patterns.pdf
Basic Sentence Patterns.pdfBasic Sentence Patterns.pdf
Basic Sentence Patterns.pdf
 
Subject verb agreement
Subject verb agreementSubject verb agreement
Subject verb agreement
 
Subject_verb_agreementpp01
Subject_verb_agreementpp01Subject_verb_agreementpp01
Subject_verb_agreementpp01
 
Final version
Final versionFinal version
Final version
 
English Syntax Primer Bimestre
English Syntax Primer BimestreEnglish Syntax Primer Bimestre
English Syntax Primer Bimestre
 
Syntax (I Bimestre)
Syntax (I Bimestre)Syntax (I Bimestre)
Syntax (I Bimestre)
 
Basic Sentence Pattern.ppt
Basic Sentence Pattern.pptBasic Sentence Pattern.ppt
Basic Sentence Pattern.ppt
 
Glossary of grammatical terms
Glossary of grammatical termsGlossary of grammatical terms
Glossary of grammatical terms
 
Patterns of Sentences
Patterns of SentencesPatterns of Sentences
Patterns of Sentences
 
Verb Phrases.pdf
Verb Phrases.pdfVerb Phrases.pdf
Verb Phrases.pdf
 
Phrasal Verbs.ppt
Phrasal Verbs.pptPhrasal Verbs.ppt
Phrasal Verbs.ppt
 
Phrasal Verbs.ppt
Phrasal Verbs.pptPhrasal Verbs.ppt
Phrasal Verbs.ppt
 

Último

"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek SchlawackFwdays
 
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostLeverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostZilliz
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
Training state-of-the-art general text embedding
Training state-of-the-art general text embeddingTraining state-of-the-art general text embedding
Training state-of-the-art general text embeddingZilliz
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfRankYa
 
Story boards and shot lists for my a level piece
Story boards and shot lists for my a level pieceStory boards and shot lists for my a level piece
Story boards and shot lists for my a level piececharlottematthew16
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxNavinnSomaal
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Mattias Andersson
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
Vector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesVector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesZilliz
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupFlorian Wilhelm
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Wonjun Hwang
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Enterprise Knowledge
 
The Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfThe Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfSeasiaInfotech2
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 

Último (20)

"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
 
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostLeverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
Training state-of-the-art general text embedding
Training state-of-the-art general text embeddingTraining state-of-the-art general text embedding
Training state-of-the-art general text embedding
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdf
 
Story boards and shot lists for my a level piece
Story boards and shot lists for my a level pieceStory boards and shot lists for my a level piece
Story boards and shot lists for my a level piece
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptx
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
Vector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesVector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector Databases
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project Setup
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
 
The Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfThe Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdf
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 

Cce

  • 1. Six Sentence Patterns Sentence Patterns #1 - Noun / Verb The most basic sentence pattern is a noun followed by a verb. It's important to remember that only verbs that do not require objects are used in this sentence pattern. Examples: People work. Frank eats. This basic sentence pattern can be modified by adding a noun phrase, possessive adjective, as well as other elements. This is true for all the sentence patterns that follow. Examples: People work. -> Our employees work. Frank eats. -> My dog Frank eats. Sentence Patterns #2 - Noun / Verb / Noun The next sentence pattern builds on the first pattern and is used with nouns that can take objects. Examples: John plays softball. The boys are watching TV. Sentence Patterns #3 - Noun / Verb / Adverb The next sentence pattern builds on the first pattern by using an adverb to describe how an action is done. Examples: Thomas drives quickly. Anna doesn't sleep deeply. Sentence Patterns #4 - Noun / Linking Verb / Noun This sentence pattern uses linking verbs to link one noun to another. Linking verbs are also known as equating verbs - verbs which equate one thing with another such as 'be', 'become', 'seem', etc. Examples: Jack is a student. This seed will become an apple. Sentence Patterns #5 - Noun / Linking Verb / Adjective This sentence pattern is similar to sentence pattern #4, but uses linking verbs to link one noun to its description using an adjective. Examples: My computer is slow! Her parents seem unhappy. Sentence Patterns #6 - Noun / Verb / Noun / Noun Sentence pattern #6 is used with verbs that take both direct and indirect objects. Examples: I bought Katherine a gift. Jennifer showed Peter her car.
  • 2. SENTENCE PATTERN DEFINITION -Sentence pattern refers to the grammatical structure of English that describe how the nature of speech should be. This denotes how, when and where the use of prefixes is applicable. With the use of these patterns you will be able to recognize the necessity of punctuation in English. There are five important components in a sentence. e.g. Subject (S) Verb (V) Object (O) Complement (C) Adverbial (A) 1. SUBJECT (S) Definition : To get ‘S’ ask the quesiton ‘Who?’ before the verb. e.g. Nancy danced well (Here “Nancy” - Subject) The child broke the glass (Here “The child” - Subject) Subject (S) consists of nouns or pronouns occurs before a verb 2. VERB (V) Definition : In every sentence the most important word is the verb. A verb shows action or activity or work done. e.g. He is a doctor (“Be” form verb) Jems wrote a letter (Main verb) The baby is crying (auxiliary verb + Main verb) Verb (V) consists of (a) auxiliaries (b) finite verbs (a) Auxiliaries e.g. am, is, are ,was, were has, have, had does, do, did Modals : can, could; will, would; shall, should; may, might; must Semi-modals / Quasi Modals : dare to; need to; used to; ought to (b) Finte verbs - denote action e.g. talk, sing, write, make, dance, play, cook, leave, teach, sleep - verbs occur after the subject - vebs occur before the object 3. OBJECT (O) Definition :
  • 3. To get the object ‘O’ ask the question ‘What’ or ‘Whome’. ‘What’ is for things and ‘Whome’ is for persons. Persons may be nouns or pronouns. e.g. He bought a pen (a pen = Object) He handles the computer (computer = Object) I saw him (him = Object) Object (O) - consists of nouns or noun phrases or noun clauses (a) Do - direct object - answers the question ‘what’ e.g. S V O (what) I likes animals (b) IO - indirect object - answers the question ‘whom’ e.g. S V IO (whom) DO I gave Rosy a pen 4. COMPLEMENT (C) Definition : The words required to complete the meaning of a sentence are called Complement of the sentence. e.g. S V C He is a dentist She became a journalist It grew dark Complement (C) - from the word ‘complete’ - completes the meaning in the sentence - wihtout it the, meaning is incomplete - wihtout it the, meaning changes occurs in two pattern. (i) S V C pattern. (ii) S V O C pattern (i) In S V C pattern, the complement C - complements the subjects - tells about the subject - wihtout it the, meaning changes - without C, the sentence is incomplete or the sentence changes its meaning - use to be forms, grew, became, seems for verb e.g. S V C They are players She was angry It seems absurd (ii) In S V O C pattern - the complement tells about the object
  • 4. - the complement and object are of the same person or thing e.g. S V O C They called David a genius I found her crying They elected Michle leader Types of Complement 1. Subject Complement Definition : The complement which expresses the quality or identity or condition of the subject is called Subject Complement. e.g. She is a doctor She looks sad 2. Object Complement Definition : The complement which expresses the quality or identity or condition of an object is called Object Complement. e.g. They made her angry She called him a liar Adjunct or Adverbial Definition : To get ‘A’ ask the question why, when, where or how. The use of adverbial is optional whereas complement is essential. It has adverb phrase, adverbial clause, noun-phrase and prepositional phrase. e.g. Why? (reason) When? (Time) Where? (Place) How? (Manner) due to cold now, later here, there by bus / cycle through floods after 2 years every where through efforts under compulsion when young in the sky by mixing carefully in the morning at home by hard work Adjunct - A - answers the questions where? when? how? why? - without A, any change in the meaning of the sentence Examples of Adjuncts in sentences e.g. S V A She Comes every day - Sit here