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LegalPromptGuide.com
  • Your FREE Guide to Mastering Legal Prompt Engineering with ChatGPT
  • 1. Introduction to Legal Prompt Engineering (LPE)
  • 2. Practical Prompt Engineering Strategies & Techniques
    • 2.1. Prompt Templates
      • 2.1.1. Summarization
      • 2.1.2. Classification
      • 2.1.3. Extraction
    • 2.2. Few-Example Prompting
  • 3. Real-world Applications of Prompt Engineering in Law
  • 4. Advanced Prompt Engineering
    • 4.1. Prompt Chaining
    • 4.2. Output Parsers
      • 4.2.1. Markdown
      • 4.2.2. HTML
      • 4.2.3. Graphviz (Dot Language)
    • 4.3. ChatGPT Plugins
    • 4.4. ChatGPT Code Interpreter
  • 5. AI Model Selection and Optimization for Legal Practice
  • 6. Implementing Responsible AI Usage at Your Law Firm
  • 7. Research Corner
    • 6.1. LLMs as Tax Attorneys
    • 6.2. Prompt Engineering for Legal Judgement Prediction
  • Appendix
    • Pro Tips!
      • Pro Tip #1
    • References
    • Change Log
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  1. 4. Advanced Prompt Engineering

4.2. Output Parsers

Previous4.1. Prompt ChainingNext4.2.1. Markdown

Last updated 1 year ago

Output parsers can be used when you want to get more structured information than just text back from ChatGPT. They allow you to customize and format the text responses into different types, such as Markdown, HTML, tables, etc. Output parsers can make your life easier and cut down on the amount of copy+paste+reformatting you have to do between ChatGPT and your documents.

4.2.1. Markdown
4.2.2. HTML
4.2.3. Graphviz (Dot Language)