5 Phases of Natural Language Processing - NLP Development Company

The 5 Phases of Natural Language Processing

Natural Language Processing – Overview

  • Natural language processing (NLP) is the interactions between computers and human language, how to program computers to process and analyse large amounts of natural language data.
  • The technology can accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves.
  • NLP makes computers capable of “understanding” the contents of documents, including the contextual nuances of the language within them.
  • Most higher-level NLP applications involve aspects that emulate intelligent behavior and apparent comprehension of natural language.
  • Many different classes of machine-learning algorithms have been applied to natural-language-processing tasks.
  • These algorithms take as input a large set of “features” that are generated from the input data.

Natural Language Processing – Market Size

Natural Language Processing Market was valued at USD 11.02 Billion in 2020 and is projected to reach USD 45.79 Billion by 2028, growing at a CAGR of 19.49 % from 2021 to 2028.

Natural Language Processing – Segmentation Analysis

Natural Language Processing – Advantages

  1. Better data analysis
  2. Streamlined processes
  3. Cost-effective
  4. Empowered employees
  5. Enhanced customer experience

Natural Language Processing – 5 Phases

  1. Phase 1 – Lexical Analysis
  2. Phase 2 – Syntactic Analysis
  3. Phase 3 – Sematic Analysis
  4. Phase 4 – Discourse Analysis
  5. Phase 5 – Pragmatic Analysis

Phase 1 – Lexical Analysis

  • Lexical analysis is the process of converting a sequence of characters into a sequence of tokens.
  • A lexer is generally combined with a parser, which together analyzes the syntax of programming languages, web pages, and so forth.
  • Lexers and parsers are most often used for compilers but can be used for other computer language tools, such as pretty printers or linters.
  • Lexical analysis is also an important analysis during the early stage of natural language processing, where text or sound waves are segmented into words and other units.

Phase 2 – Syntactic Analysis

  • Parsing, syntax analysis, or syntactic analysis is the process of analyzing a string of symbols, either in natural language, computer languages, or data structures, conforming to the rules of formal grammar.
  • It is used in the analysis of computer languages, referring to the syntactic analysis of the input code into its component parts to facilitate the writing of compilers and interpreters.
  • Grammatical rules are applied to categories and groups of words, not individual words. The syntactic analysis basically assigns a semantic structure to text.
  • Syntactic analysis is a very important part of NLP that helps in understanding the grammatical meaning of any sentence.

Phase 3 – Semantic Analysis

  • Semantic Analysis attempts to understand the meaning of Natural Language.
  • Semantic Analysis of Natural Language captures the meaning of the given text while considering context, logical structuring of sentences, and grammar roles.
  • 2 parts of Semantic Analysis are (a) Lexical Semantic Analysis and (b) Compositional Semantics Analysis.
  • Semantic analysis can begin with the relationship between individual words.

Phase 4 – Discourse Analysis

  • Researchers use Discourse analysis to uncover the motivation behind a text.
  • It is useful for studying the underlying meaning of a spoken or written text as it considers the social and historical contexts.
  • Discourse analysis is a process of performing text or language analysis, involving text interpretation, and understanding the social interactions.

Phase 5 – Pragmatic Analysis

  • Pragmatic Analysis is part of the process of extracting information from text.
  • It focuses on taking a structured set of text and figuring out the actual meaning of the text.
  • It also focuses on the meaning of the words of the time and context.
  • Effects on interpretation can be measured using PA by understanding the communicative and social content.

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