Relation Extraction using Distant Superv...

Why do we want information? So that we can use it? So that our computers can use it? When we have access to rich, structured information we can make advanced applications that solve real-world pain points. In this talk, I'll present an effective approach for automatically creating knowledge bases: databases of factual, general information. This relation extraction approach centers around the idea that we can use machine learning and natural language processing to automatically recognize information as it exists in real-world, unstructured text. I'll cover the NLP tools, special ML considerations, and novel methods for creating a successful end-to-end relation extraction system. I will also cover experimental results with this system architecture in both big-data and a search-oriented environments.