1. Tokenization: breaking down text into individual words or phrases (i.e. breaking up a sentence into its component words).
2. Part-of-Speech Tagging: labeling words according to their part of speech (i.e. noun, verb, adjective, etc.).
3. Named Entity Recognition: identifying and classifying named entities (i.e. people, locations, organizations, etc.) in text.
4. Stemming and Lemmatization: reducing inflected (or sometimes derived) words to their base form (i.e. running -> run).
5. Syntax Parsing: analyzing the structure of a sentence to determine the relationships between words (i.e. subject, object, verb, etc.).
6. Semantic Analysis: understanding the meaning of a sentence by analyzing its context.
7. Sentiment Analysis: determining the sentiment of a given text (i.e. positive, negative, neutral).
8. Machine Translation: automatically translating text from one language to another.
9. Text Summarization: creating a concise summary of a large amount of text.