Should I Use HTML or Plain Text for Context in GPT-3.5-Turbo?

Below is some guidance on how to format context for GPT-3.5 Turbo:

Plain Text vs HTML

• Plain Text
  GPT-3.5 Turbo is optimized for natural language. When you provide context in plain text, there’s less extraneous markup to parse, which helps the model focus on the actual content. Plain text is also usually simpler and more concise, reducing token overhead.

• HTML
  While HTML provides a way to include structural elements like lists and tables, the model doesn’t inherently interpret HTML semantics. Instead, it treats HTML tags as additional text. This means that unless the structure is critical to the task (e.g., when the visual presentation is part of the instruction), the extra tags might actually distract rather than help.

Best Practices

• Clarity and Structure: If the context benefits from clear delineation—like clearly separated lists or tables—you might consider using Markdown instead of HTML. Markdown provides semantic structure (such as headings, bullet points, and tables) and is generally more aligned with natural language processing.

• Token Efficiency: Plain text minimizes additional tokens from tags, which is beneficial if you’re working within a specific context window limit.

Recommendation

For most tasks with GPT-3.5 Turbo, plain text or Markdown is preferable over HTML. They keep the input clear and focused on the content without introducing unnecessary tags that do not enhance the model’s understanding. Use HTML only if your specific use case requires it and you’ve found evidence through testing that it improves results.

Hope this helps!