NER Powered Semantic Search in Python

Semantic search is a compelling technology allowing us to search using abstract concepts and meaning rather than relying on specific words. However, sometimes a simple keyword search can be just as valuable — especially if we know the exact wording of what we're searching for.

Pinecone allows you to pair semantic search with a basic keyword filter. If you know that the document you're looking for contains a specific word or set of words, you simply tell Pinecone to restrict the search to only include documents with those keywords.

We even support functionality for keyword search using sets of words with AND, OR, NOT logic.

In this video, we will explore these features through a start-to-finish example of basic keyword search in Pinecone.

🌲 Code Notebook: https://github.com/pinecone-io/examples/blob/master/learn/search/semantic-search/ner-search/ner-powered-search.ipynb

🤖 AI Dev Studio: https://aurelio.ai/

👾 Discord: https://discord.gg/c5QtDB9RAP

00:00 NER Powered Semantic Search 01:19 Dependencies and Hugging Face Datasets Prep 04:18 Creating NER Entities with Transformers 07:00 Creating Embeddings with Sentence Transformers 07:48 Using Pinecone Vector Database 11:33 Indexing the Full Medium Articles Dataset 15:09 Making Queries to Pinecone 17:01 Final Thoughts ... https://www.youtube.com/watch?v=3K94GRjDG2Q