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 perform useful tasks with the natural languages that humans use.
Components of NLP:
In this section, we will learn about the different components of NLP. There are two components of NLP. The components are described below −
Natural Language Understanding (NLU)
It involves the following tasks −
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 −
Let us now see a few important terms in the NLP terminology.
· Phonology − It is study of organizing sound systematically.
· Morphology − It is a study of construction of words from primitive meaningful units.
· 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.
Steps in NLP:
This section shows the different steps in NLP.
It involves identifying and analyzing the structure of words. Lexicon of a language means the collection of words and phrases in a language. Lexical analysis is dividing the whole chunk of txt into paragraphs, sentences, and words.
Syntactic Analysis (Parsing)
It involves analysis of words in the sentence for grammar and arranging words in a manner that shows the relationship among the words. The sentence such as “The school goes to boy” is rejected by English syntactic analyzer.
It draws the exact meaning or the dictionary meaning from the text. The text is checked for meaningfulness. It is done by mapping syntactic structures and objects in the task domain. The semantic analyzer disregards sentence such as “hot ice-cream”.
The meaning of any sentence depends upon the meaning of the sentence just before it. In addition, it also brings about the meaning of immediately succeeding sentence.
During this, what was said is re-interpreted on what it actually meant. It involves deriving those aspects of language which require real world knowledge.
Python has pre developed libraries for performing Natural Language Processing tasks and you can built expert systems by using them. Most popular libraries use now a days are
To install just goto command prompt and type pip install <library name >or conda install <library name> if you are using anaconda.
Happy reading !.