I was listening to episode 34 of AI & I of Dan Shipper interviewing Simon Eskiidsen. Simon was describing one of the processes he uses with language models to learn new words and concepts. In practice, he has a prompt template that instructs the model to explain a word to him but using it in a few sentences and giving synonyms, then injects the specific word or phrase into this template.
I’ve been fiddling around with the idea of prompt templates for a while but nothing had felt quite like the right spot to apply the approach until I heard Simon explain this example.
Using llm, here is the template and approach I came up with.
How?#
Create an edit a template
llm templates edit wdefn
wdefn short for “word definition”.
Add the prompt
prompt: |
Please help me learn what this word or phrase means: $input
Under header `## Example sentences`:
- Give 3 example sentences using this word.
- Try and use historical examples, something that is going to teach me something.
- Give me something with some well known people, in physics, computer science, or other research fields.
- Please try and make the example sentences as educational as possible. I want to learn from the examples.
Under header `## Related words and concepts`:
Give me some related words, synonyms and/or concepts that are related to this word.
Output formatting:
- Output the above in markdown.
- Use unordered lists.
- Bold the word or any derivative uses of the word in the sentences you output.
- Start the response with "# $input"
No talk. Just go.
Run the prompt template
llm -t wdefn posterity
which outputs something like the following (extra fun piping it to glow):
