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.
