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| # Named entity recognition with OpenVINO™ | |
| [](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/named-entity-recognition/named-entity-recognition.ipynb) | |
| Named entity recognition (NER) is one of the most popular data processing tasks. It is a natural language processing (NLP) method that involves detecting key information in unstructured text and categorizing it into pre-defined categories. These categories or named entities refer to the key subjects of the text, such as names, locations, companies and etc. | |
| NER is a suitable method for situations when a high-level overview of a large amount of text is needed. NER can be helpful with such tasks as analyzing key information in unstructured text or automating the information extraction of large amounts of data. | |
| This tutorial shows how to perform named entity recognition using OpenVINO. We will use the pre-trained model [`elastic/distilbert-base-cased-finetuned-conll03-english`](https://huggingface.co/elastic/distilbert-base-cased-finetuned-conll03-english). It is DistilBERT based model, trained on [`conll03 english dataset`](https://huggingface.co/datasets/conll2003). The model can recognize four named entities in text: persons, locations, organizations, and names of miscellaneous entities that do not belong to the previous three groups. The model is sensitive to capital letters. | |
| To simplify the user experience, the [Hugging Face Optimum](https://huggingface.co/docs/optimum) library is used to convert the model to OpenVINO™ IR format and quantize it. | |
| ## Notebook Contents | |
| The tutorial consists of the following steps: | |
| * Download the model | |
| * Quantize and save the model in OpenVINO IR format | |
| * Prepare demo for Named Entity Recognition OpenVINO Runtime | |
| * Compare the Original and Quantized Models | |
| ## Installation Instructions | |
| This is a self-contained example that relies solely on its own code.</br> | |
| We recommend running the notebook in a virtual environment. You only need a Jupyter server to start. | |
| For details, please refer to [Installation Guide](../../README.md). | |
| ### See Also | |
| * [OpenVINO notebooks](https://github.com/openvinotoolkit/openvino_notebooks) | |
| * [Hugging Face Optimum](https://huggingface.co/docs/optimum) | |