Extracting specific pieces of information (slots) needed to fulfill a user's intent.
The field of AI that lets computers read, interpret, translate and generate human language, from spam filters and search to chatbots.
The basic unit of text that a language model processes, typically representing a word, subword, or character. Tokens are the fundamental building blocks for LLM input and output.
Identifying and classifying named entities (people, organizations, locations) in text into predefined categories.
Building systems that learn patterns from data instead of following hand-written rules, getting better at a task as they see more examples.
Learning from examples paired with the correct answer, so a model can predict answers for new inputs it hasn't seen.
A supervised learning task where the model assigns each input to one of a fixed set of categories, such as spam or not spam.
Assigning categories or labels to text documents, a fundamental NLP task.
Identifying the user's intention or goal from their utterance in dialogue systems.
Extracting specific pieces of information (slots) needed to fulfill a user’s intent.
This concept is essential for understanding natural language processing and forms a key part of modern AI systems.
Leads to
Nothing yet: a destination in its own right.