Parsing in AI refers to the process of analyzing and breaking down a sentence, phrase, or other form of natural language into its component parts, with the goal of understanding the intended meaning. It is a crucial step in natural language processing (NLP) and is used to extract information, identify relationships between words, and translate text into a structured representation. It is essential in developing question-answering systems, machine translation, and text classification.
There are two main types of parsing: syntactic parsing and semantic parsing. Syntactic parsing analyzes the grammatical structure of a sentence and determines the relationships between words and phrases. Semantic parsing goes a step further and assigns meaning to the structured representation created by syntactic parsing.
Natural Language Processing (NLP)
Natural Language Processing (NLP) is a branch of computer science that enables machines to interpret and comprehend human language for various tasks.
Semantics in AI refers to the meaning behind words and sentences and how computers understand that meaning.
Generative Question Answering (GQA)
GQA is an AI capability that involves generating new and contextually relevant answers to questions by synthesizing information from various sources.