Natural Language Processing

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Natural Language Processing is a field of computer science that deals with text from human languages, both spoken and written. A common NLP task is translating spoken words to written text, a relatively well-solved problem is part-of-speech tagging, where a computer can correctly identify the parts of speech of each word in a sentence.

The goal of NLP is to accomplish human-like language processing. The choice of the word ‘processing’ is very deliberate, and should not be replaced with ‘understanding’[1]. Although the field of NLP was originally referred to as Natural Language Understanding (NLU) in the early days of AI, it is well agreed today that while the goal of NLP is true NLU, that goal has not yet been accomplished. A full NLU System would be able to paraphrase an input text, translate the text into another language, answer questions about the contents of the text, and draw inferences from the text.

While NLP has made serious inroads into accomplishing goals 1 to 3, the fact that NLP systems cannot, of themselves, draw inferences from text, NLU still remains the goal of NLP.[2] There are many other applications of natural language processing, including producing a summary of a block of text, optical character recognition, handwriting recognition, sentiment analysis, and machine translation.


  1. Definition of Natural Language Processing. Center for Natural Language Processing. The School of Information Studies. Syracuse University. Accessed Oct 2011.
  2. Ibid.