A natural language query is input that consists solely of terms or phrases spoken normally or entered as they might be spoken, without any non-language characters, such as the plus symbol or the asterisk, and without any special format or alteration of syntax. Natural language queries may be conducted through a text or voice interface.
Natural language processing (NLP) makes it possible for software to “understand” typical human speech or written content as input and possibly respond to it, depending on the application. A virtual assistant, for example, is designed to respond to spoken input or text. However, no software is capable of actually deriving meaning from human language as it is spoken, so NLP involves processes to translate language between the two.
NLP applies syntax techniques such as parsing for a grammatical analysis, word segmentation to break text up into smaller units, sentence breaking to apply meaningful boundaries in unbroken text, morphological segmentation to identify the structure and form of words and stemming, reducing words to the stems to which suffixes and prefixes attach. In addition to these processes, NLP uses techniques including named entity recognition (NER) and word sense disambiguation to understand input user queries, translate and return them as human-understandable responses through natural language generation (NLG).