A new notebook exploring Semantic Entity Resolution & Extraction using DSPy and Google's new LangExtract library.
Just released a new notebook exploring Semantic Entity Resolution & Extraction using DSPy (Community) and Google's new LangExtract library.
Inspired by Russell Jurney’s excellent work on semantic entity resolution, this demo follows his approach of combining:
✅ embeddings,
✅ kNN blocking,
✅ and LLM matching with DSPy (Community).
On top of that, I added a general extraction layer to test-drive LangExtract, a Gemini-powered, open-source Python library for reliable structured information extraction. The goal? Detect and merge mentions of the same real-world entities across text.
It’s an end-to-end flow tackling one of the most persistent data challenges.
Check it out, experiment with your own data, 𝐞𝐧𝐣𝐨𝐲 𝐭𝐡𝐞 𝐬𝐮𝐦𝐦𝐞𝐫 and let me know your thoughts!
cc Paco Nathan you might like this 😉
https://wor.ai/8kQ2qa
a new notebook exploring Semantic Entity Resolution & Extraction using DSPy (Community) and Google's new LangExtract library.
