Ch-12 : Natural Language Processing
Q1: Describe Natural Language Processing?
Natural Language Processing (NLP) refers to AI method of communicating with intelligent systems
using a natural language such as English.
Processing of Natural Language is required when you want an intelligent system like robot to perform
as per your instructions, when you want to hear decision from a dialogue based clinical expert system,
etc.
The field of NLP involves making computers to perform useful tasks with the natural languages
humans use. The input and output of an NLP system can be −
Speech
Written Text
There are two components of NLP as given −
Natural Language Understanding (NLU)
Understanding involves the following tasks − Mapping the given input in natural language into useful
representations and Analyzing different aspects of the language.
Natural Language Generation (NLG)
It is the process of producing meaningful phrases and sentences in the form of natural language from
some internal representation. It involves −
Text planning − It includes retrieving the relevant content from knowledge base.
Sentence planning − It includes choosing required words, forming meaningful phrases, setting tone
of the sentence.
Text Realization − It is mapping sentence plan into sentence structure.
The NLU is harder than NLG.
Difficulties in NLU
NL has an extremely rich form and structure.
It is very ambiguous. There can be different levels of ambiguity −
Lexical ambiguity − It is at very primitive level such as word-level.
, For example, treating the word “board” as noun or verb?
Syntax Level ambiguity − A sentence can be parsed in different ways.
For example, “He lifted the beetle with red cap.” − Did he use cap to lift the beetle or he lifted a
beetle that had red cap?
Referential ambiguity − Referring to something using pronouns. For example, Rima went to
Gauri. She said, “I am tired.” − Exactly who is tired?
One input can mean different meanings.
Many inputs can mean the same thing.
NLP Terminology
Phonology − It is study of organizing sound systematically.
Morphology − It is a study of construction of words from primitive meaningful units.
Morpheme − It is primitive unit of meaning in a language.
Syntax − It refers to arranging words to make a sentence. It also involves determining the
structural role of words in the sentence and in phrases.
Semantics − It is concerned with the meaning of words and how to combine words into
meaningful phrases and sentences.
Pragmatics − It deals with using and understanding sentences in different situations and how the
interpretation of the sentence is affected.
Discourse − It deals with how the immediately preceding sentence can affect the interpretation of
the next sentence.
World Knowledge − It includes the general knowledge about the world.
Q1: Describe Natural Language Processing?
Natural Language Processing (NLP) refers to AI method of communicating with intelligent systems
using a natural language such as English.
Processing of Natural Language is required when you want an intelligent system like robot to perform
as per your instructions, when you want to hear decision from a dialogue based clinical expert system,
etc.
The field of NLP involves making computers to perform useful tasks with the natural languages
humans use. The input and output of an NLP system can be −
Speech
Written Text
There are two components of NLP as given −
Natural Language Understanding (NLU)
Understanding involves the following tasks − Mapping the given input in natural language into useful
representations and Analyzing different aspects of the language.
Natural Language Generation (NLG)
It is the process of producing meaningful phrases and sentences in the form of natural language from
some internal representation. It involves −
Text planning − It includes retrieving the relevant content from knowledge base.
Sentence planning − It includes choosing required words, forming meaningful phrases, setting tone
of the sentence.
Text Realization − It is mapping sentence plan into sentence structure.
The NLU is harder than NLG.
Difficulties in NLU
NL has an extremely rich form and structure.
It is very ambiguous. There can be different levels of ambiguity −
Lexical ambiguity − It is at very primitive level such as word-level.
, For example, treating the word “board” as noun or verb?
Syntax Level ambiguity − A sentence can be parsed in different ways.
For example, “He lifted the beetle with red cap.” − Did he use cap to lift the beetle or he lifted a
beetle that had red cap?
Referential ambiguity − Referring to something using pronouns. For example, Rima went to
Gauri. She said, “I am tired.” − Exactly who is tired?
One input can mean different meanings.
Many inputs can mean the same thing.
NLP Terminology
Phonology − It is study of organizing sound systematically.
Morphology − It is a study of construction of words from primitive meaningful units.
Morpheme − It is primitive unit of meaning in a language.
Syntax − It refers to arranging words to make a sentence. It also involves determining the
structural role of words in the sentence and in phrases.
Semantics − It is concerned with the meaning of words and how to combine words into
meaningful phrases and sentences.
Pragmatics − It deals with using and understanding sentences in different situations and how the
interpretation of the sentence is affected.
Discourse − It deals with how the immediately preceding sentence can affect the interpretation of
the next sentence.
World Knowledge − It includes the general knowledge about the world.
