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Panel: NLP in Practice

If you read blog posts from tech giants, their most-cited academic papers, or major news stories about them, the current state of natural language seems to be a glorious thing, largely determined by a handful of top AI research teams in the world, and dominated by large ML models that can do almost anything imaginable.

However, if you have actual work to accomplish using NLP tools, and are held accountable to measures such as “return on investment” or “customer feedback” then you’re probably aware that the preceding sketch of the industry is abjectly false.

What is the current state of using NLP in practice? This panel, moderated by Paco Nathan and featuring technologists who’ve been building NLP apps in industry and government, cuts through the vendor marketing hype and explores the concerns from NLP practitioners’ perspective.

Disambiguation – Linking Data Science and Engineering

Disambiguation or Entity Linking is the assignment of a knowledge base identifier (Wikidata, Wikipedia) to a named entity. Our goal was to...