What is symbolic AI and how is it used in NLP?

What is symbolic AI and how is it used in NLP?

Symbolic AI refers to the use of symbols and rules to represent knowledge and reasoning. In NLP, it's used for tasks like parsing and understanding language structure.

Can you give me an example of symbolic AI in action?

Sure! An example is using a knowledge graph to represent relationships between words and concepts, allowing for better context understanding.

How does symbolic AI compare to machine learning in NLP?

Symbolic AI focuses on explicit rules and logic, while machine learning relies on data-driven approaches. They can complement each other.

What are the limitations of symbolic AI in NLP?

Limitations include difficulty in handling ambiguity and the need for extensive knowledge engineering, which can be time-consuming.

Is symbolic AI still relevant today?

Yes, it remains relevant, especially in areas requiring explainability and structured reasoning, complementing modern machine learning techniques.