Finding and classifying the mentions of the things named in text, often called Named Entity Recognition or NER, is a fundamental task in many search and analysis applications. Mature, robust NER technology is available for many languages and domains, from people, places, and products, to diseases, genes, and molecules. However, for emerging tasks like knowledge-base construction, mentions alone are insufficient.
In this presentation we’ll explore techniques that go beyond names to:
link mentions to one another and to rich knowledge sources like Wikidata
discover and characterise the relationships between entities that are explicit in the text
And we’ll discuss some of the most important practical implications of these advancements for open data science.
Presenter Bio
As Vice President of Product Management at Basis Technology, Mr. Stewart helps to drive company strategy and ensure that the company’s offerings stay ahead of the curve. Previously Mr. Stewart was the CTO of a storage services startup and a strategy consultant. He holds a Masters in Natural Language Processing from the University of Edinburgh, a BA in PPE from the University of Oxford, and a Masters from the London School of Economics.
