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NER

How to Create a Custom NER in Spacy 3.5 | by Angelica Lo Duca | Apr, 2023

Natural Language ProcessingA quick tutorial on extracting custom entities from a textPhoto by Max Chen on UnsplashAre you tired of using generic named entity recognition (NER) models that don’t quite fit your specific needs? Look no further! This article will guide you through creating a custom NER in Spacy 3.5.With a few tweaks and training data, you can have a model that accurately identifies entities specific to your domain or use case. Say goodbye to one-size-fits-all NER models and hello to customized precision.…

Satellite, drone-based monitoring of projects in NE

In a bid for the proper and timely implementation of projects and schemes, the central government has been monitoring their progress and accuracy through satellite, drone, and mobile apps, officials said.An official of the Meghalaya-based North Eastern Space Application Centre (NESAC), said that till November, out of 588 identified projects, 562 at 1,664 different locations across the eight states, have been geo-tagged through satellite images and mobile app.The Union Ministry of Development of North Eastern Region…

Make The Most of Your Small NER Data Set by Fine-tuning Bert | by Youness Mansar | Aug, 2022

Leverage Large Language models to improve your model’s performanceImage By AuthorTraining NER models on small data sets can be a pain. It can be difficult to build a model that generalizes well on a non-trivial NER task when it is trained on a few hundred samples only. This kind of problem we will try to solve in this post.First, we will define the task. Then, we will describe the different variations of the model’s architecture, and then compare the results between a pre-trained model vs one that was trained from…

Improving the NER model with patent texts | SpaCy, Prodigy and a bit of magic 🪄 | by Nikita Kiselov | Jun, 2022

Named-entity recognition (NER) — is a subtask of information extraction that seeks to locate and classify named entities … into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.… NER is also known simply as entity identification, entity chunking and entity extraction.In a nutshell, we recognise meaningful entities in the text and classify them according to the categories.Why is it useful?It can be helpfull in many areas:HR…