Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language. In particular, how to program computers to process and analyze large amounts of natural language data. Challenges in natural language processing frequently involve speech recognition, natural language understanding, and natural language generation.
Navigate to the tabs located above to perform NLP tasks such as:
Regular expressions are sequences of characters that define a search pattern. They are commonly used for string matching within search engines, find-and-replace dialogs of word processors, and input validation.
Lemmatization is the process of reducing inflected words to their word stem, base or root form. Unlike stemming, lemmatization considers the context and part of speech of the word.
Part of Speech Tagging (POS) is the process of marking each word in a text as corresponding to a particular part of speech, based on its definition and its context.
Named Entity Recognition (NER) is a subtask of information extraction that classifies named entities into predefined categories such as person names, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.