A symbolic methodology is an approach to developing AI systems for NLP based on a deterministic, conditional approach. In other words, a symbolic approach designs a system using very specific, narrow instructions that guarantee the recognition of a linguistic pattern. Rule-based solutions tend to have a high degree of precision, though they may require more work than ML-based solutions to cover the entire scope of a problem, depending on the application.
Want to learn more about symbolic methodology? Read our blog post “The Case for Symbolic AI in NLP Models“.