SlideShare a Scribd company logo
1 of 17
Natural Language Processing
Artificial Intelligence
Natural Language Processing, topics : Introduction, definition,
formal language, linguistic and language processing, terms
related to linguistic analysis, grammatical structure of
utterances - sentence, constituents, phrases, classifications
and structural rules; Syntactic Processing - context free
grammar (CFG), terminal, non-terminal and start symbols,
parser, Semantics and Pragmatics.
What is NLP ?
 NLP is Natural Language Processing. Natural
languages are those spoken by people.
 NLP encompasses anything a computer
needs to understand natural language (typed or
spoken) and also generate the natural language.
 Natural Language Processing (NLP) is a subfield
of Artificial intelligence and linguistic, devoted to
make computers "understand" statements
written in human languages.
Natural Language
• A natural language (or ordinary language) is a
language that is spoken, written by humans
for general-purpose communication.
• Example : Hindi, English, French, and Chinese,
etc.
• A language is a system, a set of symbols and a
set of rules (or grammar).
-The Symbols are combined to convey new information.
-The Rules govern the manipulation of symbols.
Natural Language Processing (NLP)
• NLP encompasses anything a computer needs
to understand natural language (typed or
spoken) and also generate the natural language.
‡ Natural Language Understanding (NLU) :
The NLU task is understanding and reasoning while
the input is a natural language.
‡ Natural Language Generation (NLG) :
• NLG is a subfield of natural language processing
NLP. NLG is also referred to text generation.
Natural Language Processing (NLP)
Formal Language
• Before defining formal language Language, we need to
define symbols, alphabets, strings and words.
• Symbol is a character, an abstract entity that has no
meaning by itself. e.g., Letters, digits and special
characters.
• Alphabet is finite set of symbols;
• an alphabet is often denoted by Σ (sigma)
• e.g. B = {0, 1} says B is an alphabet of two symbols, 0
and 1.
• C = {a, b, c} says C is an alphabet of three symbols, a, b
and c.
Continue..
• String or a word is a finite sequence of
symbols from an alphabet.
• e.g. 01110 and 111 are strings from the
alphabetB above.
• aaabccc and b are strings from the alphabet
C above.
• Language is a set of strings from an alphabet .
Con…
• Formal language (or simply language) is a set
L of strings over some finite alphabet Ƹ.
• Formal language is described using formal
grammars.
Linguistic and Language Processing
• Linguistics is the science of language. Its study
includes :
• sounds (phonology),
• word formation (morphology),
• sentence structure (syntax),
• meaning (semantics), and understanding (pragmatics)
etc.
Linguistic and Language Processing
• The levels of linguistic analysis are shown
below.
• higher level corresponds to Speech Recognition (SR)
• Lower levels corresponds to Natural Language
Processing (NLP).
Linguistic and Language Processing
Linguistic and Language Processing
Steps of Natural Language Processing (NLP)
• Natural Language Processing is done at 5 levels, as
shown in the previous slide. These levels are briefly
stated below.
Morphological and Lexical Analysis :
• The lexicon of a language is its vocabulary, that include
its words and expressions. Morphology is the
identification, analysis and description of structure of
words. The words are generally accepted as being the
smallest units of syntax. The syntax refers to the rules
and principles that govern the sentence structure of
any individual language.
Continue
• Lexical analysis: The aim is to divide the text into paragraphs,
sentences and words. the lexical analysis can not be
performed in isolation from morphological and syntactic
analysis.
• Syntactic Analysis :
Here the analysis is of words in a sentence to know the
grammatical structure of the sentence. The words are
transformed into structures that show how the words relate
to each others. Some word sequences may be rejected if they
violate the rules of the language for how words may be
combined.
• Example : An English syntactic analyzer would reject the
sentence say :
• " Boy the go the to store ".
Continue
Semantic Analysis :
• It derives an absolute (dictionary definition) meaning
from context; it determines the possible meanings of
a sentence in a context.
• The structures created by the syntactic analyzer are
assigned meaning. Thus, a mapping is made between
the syntactic structures and objects in the task domain.
The structures for which no such mapping is possible
are rejected.
• Example : the sentence "Colorless green ideas . . . " would be
rejected as semantically anomalous because colorless
and green make no sense.
Continue
Discourse Integration :
• The meaning of an individual sentence may
depend on the sentences that precede it and
may influence the meaning of the sentences
that follow it.
• Example : the word " it " in the sentence, "you
wanted it" depends on the prior discourse
context.
Continue
• Pragmatic analysis :
• It derives knowledge from external
commonsense information; it means
understanding the purposeful use of language in
situations, particularly those aspects of language
which require world knowledge; The idea is, what
was said is reinterpreted to determine what was
actually meant. Example : the sentence
• "Do you know what time it is ?“
should be interpreted as a request.

More Related Content

What's hot

Language and its components
Language and its componentsLanguage and its components
Language and its componentsMIMOUN SEHIBI
 
[Andrew spencer] morphological_theory(book_fi.org) for taha
[Andrew spencer] morphological_theory(book_fi.org) for taha [Andrew spencer] morphological_theory(book_fi.org) for taha
[Andrew spencer] morphological_theory(book_fi.org) for taha Zainab Dahou
 
Natural Language Ambiguity and its Effect on Machine Learning
Natural Language Ambiguity and its Effect on Machine LearningNatural Language Ambiguity and its Effect on Machine Learning
Natural Language Ambiguity and its Effect on Machine LearningIJMER
 
Spoken vs written epr
Spoken vs written eprSpoken vs written epr
Spoken vs written eprnivre888
 
Speaking another language
Speaking another languageSpeaking another language
Speaking another languageyounes Anas
 
Types of corpus linguistics Parallel ,aligned...
 Types of corpus linguistics Parallel ,aligned... Types of corpus linguistics Parallel ,aligned...
Types of corpus linguistics Parallel ,aligned...RajpootBhatti5
 
Principles of parameters
Principles of parametersPrinciples of parameters
Principles of parametersVelnar
 
Collaborative work 1 language forms and function
Collaborative work 1 language forms and functionCollaborative work 1 language forms and function
Collaborative work 1 language forms and functionMaría Ortega
 
Language and Knowledge: Against Modularity as a Viable Theory of Language an...
Language and Knowledge: Against Modularity  as a Viable Theory of Language an...Language and Knowledge: Against Modularity  as a Viable Theory of Language an...
Language and Knowledge: Against Modularity as a Viable Theory of Language an...Dominik Lukes
 
Distributed morphology.
Distributed morphology.Distributed morphology.
Distributed morphology.1101989
 
Language descriptions
Language descriptionsLanguage descriptions
Language descriptionsthuhong143
 
Syntax and lexis presentation final 3
Syntax and lexis presentation final 3Syntax and lexis presentation final 3
Syntax and lexis presentation final 3mohamed oubedda
 
Chapter 3 The Process of Translation Chapter 3
Chapter 3 The Process of Translation Chapter 3Chapter 3 The Process of Translation Chapter 3
Chapter 3 The Process of Translation Chapter 3Ivet Sanchez
 
Applied Linguistics "Grammar"
Applied Linguistics "Grammar"Applied Linguistics "Grammar"
Applied Linguistics "Grammar"Kum Visal
 
Discourse & Culture
Discourse & CultureDiscourse & Culture
Discourse & CultureLaiba Yaseen
 
Translation and Language Functions
Translation and Language FunctionsTranslation and Language Functions
Translation and Language FunctionsUniversity of Panama
 

What's hot (20)

Language and its components
Language and its componentsLanguage and its components
Language and its components
 
[Andrew spencer] morphological_theory(book_fi.org) for taha
[Andrew spencer] morphological_theory(book_fi.org) for taha [Andrew spencer] morphological_theory(book_fi.org) for taha
[Andrew spencer] morphological_theory(book_fi.org) for taha
 
Natural Language Ambiguity and its Effect on Machine Learning
Natural Language Ambiguity and its Effect on Machine LearningNatural Language Ambiguity and its Effect on Machine Learning
Natural Language Ambiguity and its Effect on Machine Learning
 
The Three Grammars
The Three GrammarsThe Three Grammars
The Three Grammars
 
Spoken vs written epr
Spoken vs written eprSpoken vs written epr
Spoken vs written epr
 
Speaking another language
Speaking another languageSpeaking another language
Speaking another language
 
Types of corpus linguistics Parallel ,aligned...
 Types of corpus linguistics Parallel ,aligned... Types of corpus linguistics Parallel ,aligned...
Types of corpus linguistics Parallel ,aligned...
 
What is grammar
What is grammarWhat is grammar
What is grammar
 
Principles of parameters
Principles of parametersPrinciples of parameters
Principles of parameters
 
Collaborative work 1 language forms and function
Collaborative work 1 language forms and functionCollaborative work 1 language forms and function
Collaborative work 1 language forms and function
 
Language and Knowledge: Against Modularity as a Viable Theory of Language an...
Language and Knowledge: Against Modularity  as a Viable Theory of Language an...Language and Knowledge: Against Modularity  as a Viable Theory of Language an...
Language and Knowledge: Against Modularity as a Viable Theory of Language an...
 
Distributed morphology.
Distributed morphology.Distributed morphology.
Distributed morphology.
 
Language descriptions
Language descriptionsLanguage descriptions
Language descriptions
 
Syntax and lexis presentation final 3
Syntax and lexis presentation final 3Syntax and lexis presentation final 3
Syntax and lexis presentation final 3
 
Chapter 3 The Process of Translation Chapter 3
Chapter 3 The Process of Translation Chapter 3Chapter 3 The Process of Translation Chapter 3
Chapter 3 The Process of Translation Chapter 3
 
NLP_KASHK:POS Tagging
NLP_KASHK:POS TaggingNLP_KASHK:POS Tagging
NLP_KASHK:POS Tagging
 
Parameter setting
Parameter settingParameter setting
Parameter setting
 
Applied Linguistics "Grammar"
Applied Linguistics "Grammar"Applied Linguistics "Grammar"
Applied Linguistics "Grammar"
 
Discourse & Culture
Discourse & CultureDiscourse & Culture
Discourse & Culture
 
Translation and Language Functions
Translation and Language FunctionsTranslation and Language Functions
Translation and Language Functions
 

Similar to Nlp

Natural language processing
Natural language processingNatural language processing
Natural language processingSaurav Aryal
 
5810 oral lang anly transcr wkshp (fall 2014) pdf
5810 oral lang anly transcr wkshp (fall 2014) pdf  5810 oral lang anly transcr wkshp (fall 2014) pdf
5810 oral lang anly transcr wkshp (fall 2014) pdf SVTaylor123
 
Natural language processing
Natural language processingNatural language processing
Natural language processingBasha Chand
 
NLP_KASHK:Context-Free Grammar for English
NLP_KASHK:Context-Free Grammar for EnglishNLP_KASHK:Context-Free Grammar for English
NLP_KASHK:Context-Free Grammar for EnglishHemantha Kulathilake
 
Linguistics notes 1
Linguistics notes 1Linguistics notes 1
Linguistics notes 1h4976
 
Natural Language Processing - Unit 1
Natural Language Processing - Unit 1Natural Language Processing - Unit 1
Natural Language Processing - Unit 1Mithun B N
 
Engineering Intelligent NLP Applications Using Deep Learning – Part 1
Engineering Intelligent NLP Applications Using Deep Learning – Part 1Engineering Intelligent NLP Applications Using Deep Learning – Part 1
Engineering Intelligent NLP Applications Using Deep Learning – Part 1Saurabh Kaushik
 
Computational linguistics
Computational linguisticsComputational linguistics
Computational linguisticsshrey bhate
 
Natural language processing (nlp)
Natural language processing (nlp)Natural language processing (nlp)
Natural language processing (nlp)Kuppusamy P
 
Linguistics
LinguisticsLinguistics
LinguisticsAna K
 
01-Intro.pdf
01-Intro.pdf01-Intro.pdf
01-Intro.pdfyesufali2
 

Similar to Nlp (20)

Nlp
NlpNlp
Nlp
 
Natural Language Processing.pptx
Natural Language Processing.pptxNatural Language Processing.pptx
Natural Language Processing.pptx
 
Natural Language Processing
Natural Language ProcessingNatural Language Processing
Natural Language Processing
 
Natural language processing
Natural language processingNatural language processing
Natural language processing
 
NLP
NLPNLP
NLP
 
5810 oral lang anly transcr wkshp (fall 2014) pdf
5810 oral lang anly transcr wkshp (fall 2014) pdf  5810 oral lang anly transcr wkshp (fall 2014) pdf
5810 oral lang anly transcr wkshp (fall 2014) pdf
 
Natural language processing
Natural language processingNatural language processing
Natural language processing
 
REPORT.doc
REPORT.docREPORT.doc
REPORT.doc
 
NLP_KASHK:Context-Free Grammar for English
NLP_KASHK:Context-Free Grammar for EnglishNLP_KASHK:Context-Free Grammar for English
NLP_KASHK:Context-Free Grammar for English
 
Linguistics notes 1
Linguistics notes 1Linguistics notes 1
Linguistics notes 1
 
L1 nlp intro
L1 nlp introL1 nlp intro
L1 nlp intro
 
1 Introduction.ppt
1 Introduction.ppt1 Introduction.ppt
1 Introduction.ppt
 
Syntax course
Syntax courseSyntax course
Syntax course
 
Natural Language Processing - Unit 1
Natural Language Processing - Unit 1Natural Language Processing - Unit 1
Natural Language Processing - Unit 1
 
Engineering Intelligent NLP Applications Using Deep Learning – Part 1
Engineering Intelligent NLP Applications Using Deep Learning – Part 1Engineering Intelligent NLP Applications Using Deep Learning – Part 1
Engineering Intelligent NLP Applications Using Deep Learning – Part 1
 
Syntactic Structures
Syntactic StructuresSyntactic Structures
Syntactic Structures
 
Computational linguistics
Computational linguisticsComputational linguistics
Computational linguistics
 
Natural language processing (nlp)
Natural language processing (nlp)Natural language processing (nlp)
Natural language processing (nlp)
 
Linguistics
LinguisticsLinguistics
Linguistics
 
01-Intro.pdf
01-Intro.pdf01-Intro.pdf
01-Intro.pdf
 

More from Ahmad sohail Kakar (20)

Lec 1 network types
Lec 1 network typesLec 1 network types
Lec 1 network types
 
Lec 1 introduction
Lec 1 introductionLec 1 introduction
Lec 1 introduction
 
Active directory restoration
Active directory restorationActive directory restoration
Active directory restoration
 
Active directory backup
Active directory backupActive directory backup
Active directory backup
 
Seii unit7 component-level-design
Seii unit7 component-level-designSeii unit7 component-level-design
Seii unit7 component-level-design
 
Seii unit6 software-testing-techniques
Seii unit6 software-testing-techniquesSeii unit6 software-testing-techniques
Seii unit6 software-testing-techniques
 
Seii unit5 ui_design
Seii unit5 ui_designSeii unit5 ui_design
Seii unit5 ui_design
 
Seii unit4 software_process
Seii unit4 software_processSeii unit4 software_process
Seii unit4 software_process
 
Se ii unit3-architectural-design
Se ii unit3-architectural-designSe ii unit3-architectural-design
Se ii unit3-architectural-design
 
Se ii unit2-software_design_principles
Se ii unit2-software_design_principlesSe ii unit2-software_design_principles
Se ii unit2-software_design_principles
 
Se ii unit1-se_ii_intorduction
Se ii unit1-se_ii_intorductionSe ii unit1-se_ii_intorduction
Se ii unit1-se_ii_intorduction
 
Second chapter-java
Second chapter-javaSecond chapter-java
Second chapter-java
 
Second chapter-java
Second chapter-javaSecond chapter-java
Second chapter-java
 
Chapter 9 java
Chapter 9 javaChapter 9 java
Chapter 9 java
 
Chapter 8 java
Chapter 8 javaChapter 8 java
Chapter 8 java
 
Chapter 7 java
Chapter 7 javaChapter 7 java
Chapter 7 java
 
Chapter 6 java
Chapter 6 javaChapter 6 java
Chapter 6 java
 
Chapter 5 java
Chapter 5 javaChapter 5 java
Chapter 5 java
 
Chapter 4 java
Chapter 4 javaChapter 4 java
Chapter 4 java
 
Chapter 3 java
Chapter 3 javaChapter 3 java
Chapter 3 java
 

Recently uploaded

Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxEmployee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxNirmalaLoungPoorunde1
 
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdfFraming an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdfUjwalaBharambe
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxpboyjonauth
 
Earth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice greatEarth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice greatYousafMalik24
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxmanuelaromero2013
 
Meghan Sutherland In Media Res Media Component
Meghan Sutherland In Media Res Media ComponentMeghan Sutherland In Media Res Media Component
Meghan Sutherland In Media Res Media ComponentInMediaRes1
 
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,Virag Sontakke
 
Computed Fields and api Depends in the Odoo 17
Computed Fields and api Depends in the Odoo 17Computed Fields and api Depends in the Odoo 17
Computed Fields and api Depends in the Odoo 17Celine George
 
Pharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfPharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfMahmoud M. Sallam
 
MARGINALIZATION (Different learners in Marginalized Group
MARGINALIZATION (Different learners in Marginalized GroupMARGINALIZATION (Different learners in Marginalized Group
MARGINALIZATION (Different learners in Marginalized GroupJonathanParaisoCruz
 
KSHARA STURA .pptx---KSHARA KARMA THERAPY (CAUSTIC THERAPY)————IMP.OF KSHARA ...
KSHARA STURA .pptx---KSHARA KARMA THERAPY (CAUSTIC THERAPY)————IMP.OF KSHARA ...KSHARA STURA .pptx---KSHARA KARMA THERAPY (CAUSTIC THERAPY)————IMP.OF KSHARA ...
KSHARA STURA .pptx---KSHARA KARMA THERAPY (CAUSTIC THERAPY)————IMP.OF KSHARA ...M56BOOKSTORE PRODUCT/SERVICE
 
internship ppt on smartinternz platform as salesforce developer
internship ppt on smartinternz platform as salesforce developerinternship ppt on smartinternz platform as salesforce developer
internship ppt on smartinternz platform as salesforce developerunnathinaik
 
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxProudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxthorishapillay1
 
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Celine George
 
CELL CYCLE Division Science 8 quarter IV.pptx
CELL CYCLE Division Science 8 quarter IV.pptxCELL CYCLE Division Science 8 quarter IV.pptx
CELL CYCLE Division Science 8 quarter IV.pptxJiesonDelaCerna
 
DATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginnersDATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginnersSabitha Banu
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course  for BeginnersFull Stack Web Development Course  for Beginners
Full Stack Web Development Course for BeginnersSabitha Banu
 

Recently uploaded (20)

Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxEmployee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptx
 
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdfFraming an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
 
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
 
ESSENTIAL of (CS/IT/IS) class 06 (database)
ESSENTIAL of (CS/IT/IS) class 06 (database)ESSENTIAL of (CS/IT/IS) class 06 (database)
ESSENTIAL of (CS/IT/IS) class 06 (database)
 
Earth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice greatEarth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice great
 
OS-operating systems- ch04 (Threads) ...
OS-operating systems- ch04 (Threads) ...OS-operating systems- ch04 (Threads) ...
OS-operating systems- ch04 (Threads) ...
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptx
 
Meghan Sutherland In Media Res Media Component
Meghan Sutherland In Media Res Media ComponentMeghan Sutherland In Media Res Media Component
Meghan Sutherland In Media Res Media Component
 
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
 
Computed Fields and api Depends in the Odoo 17
Computed Fields and api Depends in the Odoo 17Computed Fields and api Depends in the Odoo 17
Computed Fields and api Depends in the Odoo 17
 
Pharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfPharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdf
 
MARGINALIZATION (Different learners in Marginalized Group
MARGINALIZATION (Different learners in Marginalized GroupMARGINALIZATION (Different learners in Marginalized Group
MARGINALIZATION (Different learners in Marginalized Group
 
KSHARA STURA .pptx---KSHARA KARMA THERAPY (CAUSTIC THERAPY)————IMP.OF KSHARA ...
KSHARA STURA .pptx---KSHARA KARMA THERAPY (CAUSTIC THERAPY)————IMP.OF KSHARA ...KSHARA STURA .pptx---KSHARA KARMA THERAPY (CAUSTIC THERAPY)————IMP.OF KSHARA ...
KSHARA STURA .pptx---KSHARA KARMA THERAPY (CAUSTIC THERAPY)————IMP.OF KSHARA ...
 
internship ppt on smartinternz platform as salesforce developer
internship ppt on smartinternz platform as salesforce developerinternship ppt on smartinternz platform as salesforce developer
internship ppt on smartinternz platform as salesforce developer
 
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxProudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptx
 
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
 
CELL CYCLE Division Science 8 quarter IV.pptx
CELL CYCLE Division Science 8 quarter IV.pptxCELL CYCLE Division Science 8 quarter IV.pptx
CELL CYCLE Division Science 8 quarter IV.pptx
 
DATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginnersDATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginners
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course  for BeginnersFull Stack Web Development Course  for Beginners
Full Stack Web Development Course for Beginners
 

Nlp

  • 1. Natural Language Processing Artificial Intelligence Natural Language Processing, topics : Introduction, definition, formal language, linguistic and language processing, terms related to linguistic analysis, grammatical structure of utterances - sentence, constituents, phrases, classifications and structural rules; Syntactic Processing - context free grammar (CFG), terminal, non-terminal and start symbols, parser, Semantics and Pragmatics.
  • 2. What is NLP ?  NLP is Natural Language Processing. Natural languages are those spoken by people.  NLP encompasses anything a computer needs to understand natural language (typed or spoken) and also generate the natural language.  Natural Language Processing (NLP) is a subfield of Artificial intelligence and linguistic, devoted to make computers "understand" statements written in human languages.
  • 3. Natural Language • A natural language (or ordinary language) is a language that is spoken, written by humans for general-purpose communication. • Example : Hindi, English, French, and Chinese, etc. • A language is a system, a set of symbols and a set of rules (or grammar). -The Symbols are combined to convey new information. -The Rules govern the manipulation of symbols.
  • 4. Natural Language Processing (NLP) • NLP encompasses anything a computer needs to understand natural language (typed or spoken) and also generate the natural language. ‡ Natural Language Understanding (NLU) : The NLU task is understanding and reasoning while the input is a natural language. ‡ Natural Language Generation (NLG) : • NLG is a subfield of natural language processing NLP. NLG is also referred to text generation.
  • 6. Formal Language • Before defining formal language Language, we need to define symbols, alphabets, strings and words. • Symbol is a character, an abstract entity that has no meaning by itself. e.g., Letters, digits and special characters. • Alphabet is finite set of symbols; • an alphabet is often denoted by Σ (sigma) • e.g. B = {0, 1} says B is an alphabet of two symbols, 0 and 1. • C = {a, b, c} says C is an alphabet of three symbols, a, b and c.
  • 7. Continue.. • String or a word is a finite sequence of symbols from an alphabet. • e.g. 01110 and 111 are strings from the alphabetB above. • aaabccc and b are strings from the alphabet C above. • Language is a set of strings from an alphabet .
  • 8. Con… • Formal language (or simply language) is a set L of strings over some finite alphabet Ƹ. • Formal language is described using formal grammars.
  • 9. Linguistic and Language Processing • Linguistics is the science of language. Its study includes : • sounds (phonology), • word formation (morphology), • sentence structure (syntax), • meaning (semantics), and understanding (pragmatics) etc.
  • 10. Linguistic and Language Processing • The levels of linguistic analysis are shown below. • higher level corresponds to Speech Recognition (SR) • Lower levels corresponds to Natural Language Processing (NLP).
  • 13. Steps of Natural Language Processing (NLP) • Natural Language Processing is done at 5 levels, as shown in the previous slide. These levels are briefly stated below. Morphological and Lexical Analysis : • The lexicon of a language is its vocabulary, that include its words and expressions. Morphology is the identification, analysis and description of structure of words. The words are generally accepted as being the smallest units of syntax. The syntax refers to the rules and principles that govern the sentence structure of any individual language.
  • 14. Continue • Lexical analysis: The aim is to divide the text into paragraphs, sentences and words. the lexical analysis can not be performed in isolation from morphological and syntactic analysis. • Syntactic Analysis : Here the analysis is of words in a sentence to know the grammatical structure of the sentence. The words are transformed into structures that show how the words relate to each others. Some word sequences may be rejected if they violate the rules of the language for how words may be combined. • Example : An English syntactic analyzer would reject the sentence say : • " Boy the go the to store ".
  • 15. Continue Semantic Analysis : • It derives an absolute (dictionary definition) meaning from context; it determines the possible meanings of a sentence in a context. • The structures created by the syntactic analyzer are assigned meaning. Thus, a mapping is made between the syntactic structures and objects in the task domain. The structures for which no such mapping is possible are rejected. • Example : the sentence "Colorless green ideas . . . " would be rejected as semantically anomalous because colorless and green make no sense.
  • 16. Continue Discourse Integration : • The meaning of an individual sentence may depend on the sentences that precede it and may influence the meaning of the sentences that follow it. • Example : the word " it " in the sentence, "you wanted it" depends on the prior discourse context.
  • 17. Continue • Pragmatic analysis : • It derives knowledge from external commonsense information; it means understanding the purposeful use of language in situations, particularly those aspects of language which require world knowledge; The idea is, what was said is reinterpreted to determine what was actually meant. Example : the sentence • "Do you know what time it is ?“ should be interpreted as a request.