Skip to Main Content
IBM Data and AI Ideas Portal for Customers


This portal is to open public enhancement requests against products and services offered by the IBM Data & AI organization. To view all of your ideas submitted to IBM, create and manage groups of Ideas, or create an idea explicitly set to be either visible by all (public) or visible only to you and IBM (private), use the IBM Unified Ideas Portal (https://ideas.ibm.com).


Shape the future of IBM!

We invite you to shape the future of IBM, including product roadmaps, by submitting ideas that matter to you the most. Here's how it works:


Search existing ideas

Start by searching and reviewing ideas and requests to enhance a product or service. Take a look at ideas others have posted, and add a comment, vote, or subscribe to updates on them if they matter to you. If you can't find what you are looking for,


Post your ideas

Post ideas and requests to enhance a product or service. Take a look at ideas others have posted and upvote them if they matter to you,

  1. Post an idea

  2. Upvote ideas that matter most to you

  3. Get feedback from the IBM team to refine your idea


Specific links you will want to bookmark for future use

Welcome to the IBM Ideas Portal (https://www.ibm.com/ideas) - Use this site to find out additional information and details about the IBM Ideas process and statuses.

IBM Unified Ideas Portal (https://ideas.ibm.com) - Use this site to view all of your ideas, create new ideas for any IBM product, or search for ideas across all of IBM.

ideasibm@us.ibm.com - Use this email to suggest enhancements to the Ideas process or request help from IBM for submitting your Ideas.

IBM Employees should enter Ideas at https://ideas.ibm.com


Status Planned for future release
Created by Guest
Created on Jul 11, 2018

Support pre-annotated document at predict time (Custom Relations)

Scope
  1. Watson Health has very good entity extractors but they are in need of relation extractors. 
  2. They would like to train a custom relations model in WKS. Since they already have good entity extractors, it doesn't make sense for them to train an entities model.
  3. The existing entity type system will be imported to WKS as part of the training.
  4. At predict time they will pass entities pre-annotated in the text and only request relations between the entities in response.
  5. The custom relations model will take the pre-annotated entities and return relations between them.