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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.

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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.