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Entity Extraction from text using Granite

Large Language Models (LLMs) have demonstrated remarkable accuracy in the task of entity extraction. This cookbook focuses on extracting key entities from descriptions related to books.

The goal of this lab is to show how you can use IBM Granite models in order to extract entity information from a document and return it in a specific format.

Prerequisites

This lab is a Jupyter notebook. Please follow the instructions in pre-work to run the lab.

Lab

Entity Extraction from text using Granite notebook Entity Extraction from text using Granite notebook

To run the notebook from your command line in Jupyter using the active virtual environment from the pre-work, run:

jupyter notebook notebooks/entity_extraction.ipynb

The path of the notebook file above is relative to the granite-workshop folder from the git clone in the pre-work.

Credits

This notebook is a modified version of the IBM Granite Community Entity Extraction from text using Granite notebook. Refer to the IBM Granite Community for the official notebooks.