IBM Watson advances natural language processing technology

By Brittany Hill

Leading provider of artificial intelligence for businesses - IBM Watson - announces new natural language processing (NLP) technologies.

The new technology is the first commercialisation of natural language processing (NLP) capabilities to come from IBM Research’s Project Debater, “the only AI system capable of debating humans on complex topics.”

IBM Watson’s new technology has been designed to help organisations to identify, understand and analyse some of the challenging aspects of the english language, driving increased clarity and improving insights. 

To create a more holistic understanding of business operations, a new feature for IBM Watson includes the abi;lity to define, identify and analyse idioms and colloquialisms for the first time. Another feature includes the ability to understand business documents such as PDF’s and contracts. 


Over the next year, IBM plans to integrate the Project Debater technology throughout Watson focusing on three core areas:


Using advanced sentiment analysis, the technology will be able to identify and understand complicated word schemes, as well as improving the technology’s understanding of business documentation.


By pulling textual data from multiple sources this technology will provide users with a summary of what is being said and written about a particular topic to provide deeper contextual understanding, which will be known as summarisation.


Building on insights from the Project Debater, advanced topic clustering techniques will enable users to cluster incoming data to create meaningful ‘topics’ which can be analysed. The technology will also allow for manipulation in order to fine tune ‘topics’ to reflect specific language.

"Language is a tool for expressing thought and opinion, as much as it is a tool for information," said Rob Thomas, General Manager, IBM Data and AI. "This is why we're harvesting technology from Project Debater and integrating it into Watson – to enable businesses to capture, analyze, and understand more from human language and start to transform how they utilize intellectual capital that's codified in data."

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