Natural language processing

How it is used

Almost always shortened to NLP in speech and job titles (NLP engineer, NLP team). Classic NLP tasks include sentiment analysis, named entity recognition and machine translation; since LLMs, many of them are handled by one general model.

Example sentences

1. Turkish is harder for natural language processing because one word can carry many suffixes.

2. She wrote her master's thesis on natural language processing for legal documents.

Common collocations

• NLP engineer
• NLP task
• NLP pipeline
• classic NLP

Related terms

• sentiment analysisAn NLP task that detects the opinion or emotion in a text, for example whether a product review is positive, negative or neutral.
• named entity recognitionAn NLP task that finds the names of people, organizations and places, as well as dates, amounts and similar items, in a text and labels each one with its type.
• tokenizerThe component that splits text into tokens and turns them into numbers a model can read, and that turns the model's output numbers back into text.
• embeddingA list of numbers (a vector) that represents a word, sentence, image or other item in such a way that items with similar meanings end up close to each other.
• LLMShort for large language model: a very large neural network trained on huge amounts of text to predict the next token, which lets it answer questions, write, summarize and code.

This word in other fields

The same English word can have a different meaning in another field:

• natural language processing · Artificial Intelligence & Machine Learning

More terms: Machine Learning and Data Processing

• artificial intelligence
• machine learning
• model
• dataset
• training data
• label
• train
• supervised learning
• neural network
• deep learning
• loss function
• overfitting