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Features
Tokenization
Identify the boundaries of words in sentences. This is the first critical processing step and the input for the next processing phases for natural language processing systems. Tokenization can be applied to data mining, searching and extracting systems
Part-of-Speech Tagging
Identify the type of labels for each word in the sentence such as noun, verb, adjective, pronoun, determinant, etc. This is the next important processing step after Tokenization, which is the basis to understand the meaning of a word, and is also the input for the next processing phases in natural language processing. Part-of-Speech Tagging can be applied to information retrieval systems
Named Entity Recognition
Identify and automatically classify the components of a document into given categories such as organization, name, location, time, currency, etc. Named Entity Recognition is used in data mining systems, questions and answers, machine translation, text summary, etc
Spell Checking
Correct spelling errors in sentences. This step will detect the wrong spellings of the writer and correct them to help natural language processing system get the right information and contribute to the accuracy of data mining, searching and extracting information