Watson Natural Language Processing Library

Bonisiwe Shabane

-Dec 28, 2025, 4:49 AM

watson natural language processing library

Assets/Accelerators for Watson NLP (this repo) contains self-serve notebooks and documentation on how to create NLP models using Watson NLP library, how to serve Watson NLP models, and how to make inference requests from... With an IBM Cloud account a full production sample can be deployed in roughly one hour. Machine Learning notebooks, tutorials, and datasets focused on supporting a Data Science Engineer are under the ML folder. Assets focused on deployment are under the MLOps folder. Go to the respective folders to learn more about these assets. Michael Spriggs, Principal Architect Shivam Solanki, Senior Advisory Data Scientist Kevin Huang, Sr.

ML-Ops Engineer Abhilasha Mangal, Senior Data Scientist Himadri Talukder - Senior Software Engineer This framework is developed by Build Lab, IBM Ecosystem. Please note that this content is made available to foster Embeddable AI technology adoption and serve ecosystem partners. The content may include systems & methods pending patent with the USPTO and protected under US Patent Laws. SuperKnowa is not a product but a framework built on the top of IBM watsonx along with other products like LLAMA models from Meta & ML Flow from Databricks. Using SuperKnowa implicitly requires agreeing to the Terms and conditions of those products.

This framework is made available on an as-is basis to accelerate Enterprise GenAI applications development. In case of any questions, please reach out to kunal@ibm.com. Watson Natural Language Processing Library for Embed is a containerized library designed to empower IBM partners with greater flexibility to infuse powerful natural language AI into their solutions. This posts summarizes some of the possible use cases for which documentation and samples are available. Scenario: Customer reviews of hotels are classified in ‘non-complaint’ and ‘complaint’ Example: “The served food was delicious, yet the service was slow.”

The block identifies that there is a positive sentiment expressed towards the target “food”, and a negative sentiment expressed towards “service”. Scenario: Classify emotions in tweets into ‘sadness’, ‘joy’, ‘anger’, ‘fear’ and ‘disgust’ There are a number of Natural Language Processing (NLP) services offered, covering a number of languages, within the IBM Watson Libraries for Embed. The model catalog lists all available models. In addition to the models there is a runtime which supports both gRPC and REST enpoints. When deploying a model you need to combine the models you want with the container and there are a number of ways to do this:

The model containers available on the IBM Container Registry do not have a runtime installed. Their default entry point is /bin/sh -c /app/unpack_model.sh, which will expand the model into directory /app/models. This means running a model container will expand the model into directory /app/models, so if this is an external volume mounted into the container the model will be on the external volume, which could... The NLP containers can get very large, with the runtime currently being 2.5GB> Startup times need to be considered when adding multiple models into a single container with the NLP runtime. Partner with IBM to embed Natural Language Processing into your solutions. Introducing IBM Watson NLP Library for Embed, a containerized library designed to empower IBM partners with greater flexibility to infuse powerful natural language AI into their solutions.

It combines the best of open source and IBM® Research® NLP algorithms to deliver superior AI capabilities developers can access and integrate into their apps in the environment of their choice. Offered to partners as embeddable AI, a first of its kind software portfolio that offers best of breed AI from IBM. Build with IBM natural language embeddable AI Watson NLP Library for Embed helps develop enterprise-ready solutions through robust AI models, extensive language coverage and scalable container orchestration. The library form provides the flexibility to deploy natural language AI in any environment. Natural language processing for advanced text analysis. Analyze various features of text content at scale.

Provide text, raw HTML, or a public URL and IBM Watson Natural Language Understanding will give you results for the features you request. The service cleans HTML content before analysis by default, so the results can ignore most advertisements and other unwanted content. Everything you need to integrate with Watson Natural Language Understanding IBM Watson's Natural Language Understanding API provides powerful features for analyzing text, including sentiment analysis, entity recognition, and keyword extraction. In this blog, we will explore how to use this API and include some example code in JavaScript. Before we start writing code, we need to obtain an API key from IBM Watson.

You can sign up for a free account on the IBM Cloud website, and then create a Natural Language Understanding instance from the catalog. Once you have the instance created, you can view your API credentials by clicking on the "Service credentials" tab. The endpoint for the Natural Language Understanding API is https://api.us-south.natural-language-understanding.watson.cloud.ibm.com. Note that the URL for your own instance may differ slightly depending on the region you selected when creating the instance. This blog post is about using the IBM Watson Natural Language Processing Library for Embed on IBM Cloud Code Engine and is related to my blog post Run Watson NLP for Embed on your... IBM Cloud Code Engine is a fully managed, serverless platform where you can run container images or batch jobs.

The IBM Watson Libraries for Embed are made for IBM Business Partners. Partners can get additional details about embeddable AI on the IBM Partner World page. If you are an IBM Business Partner you can get a free access to the IBM Watson Natural Language Processing Library for Embed. To get started with the libraries you can use the link Watson Natural Language Processing Library for Embed home. It is an awesome documentation and it is public available. I used parts of the IBM Watson documentation in my Code Engine example and I created a GitHub project with some additional example bash scripting.

The project is called Run Watson NLP for Embed on your IBM Cloud Code Engine. The IBM Watson Libraries for Embed do provide a lot of pre-trained models you can find in the related model catalog for the Watson Libraries. Here is a link to the model catalog for Watson NLP, the catalog is public available. In this session hosted by NASA's Interagency Implementation and Advanced Concepts Team (IMPACT), Sukriti Sharma from IBM presents some of IBM’s best natural language processing (NLP) technologies productionized and available in a Python embeddable... ‘Watson NLP’ is IBM’s standard NLP library, with a wide range of features with pre-trained models and support for custom training. It is cross-lingually stable across several languages (30+) and powers 10+ IBM products, supporting both high quality and high runtime performance use cases and containing innovations from IBM research and other IBM products.

Sukriti provides a broad overview of Watson NLP and deeper insights on entity extraction, text classification, and topic modeling. Sukriti Sharma is a machine learning (ML) engineer at IBM. He manages the team building a python embeddable standard NLP library, and his focus has been on experimenting with different NLP algorithms, particularly for entity extraction; model evaluation, analysis and data collection; building scalable... Sukriti has a master’s degree in computer science from North Carolina State University, with a specialization in data science.

Watson Natural Language Processing Library

People Also Search

Assets/Accelerators For Watson NLP (this Repo) Contains Self-serve Notebooks And

ML-Ops Engineer Abhilasha Mangal, Senior Data Scientist Himadri Talukder -

This Framework Is Made Available On An As-is Basis To

The Block Identifies That There Is A Positive Sentiment Expressed

The Model Containers Available On The IBM Container Registry Do