Thu, Mar 07, 2019 @ 09:30 AM - 10:30 AM
Conferences, Lectures, & Seminars
Speaker: Eunsol Choi, University of Washington
Talk Title: Learning to Understand Entities In Text
Series: CS Colloquium
Abstract: Real world entities such as people, organizations and countries play a critical role in text. Reading offers rich explicit and implicit information about these entities, such as the categories they belong to, relationships they have with other entities, and events they participate in. In this talk, we introduce approaches to infer implied information about entities, and to automatically query such information in an interactive setting. We expand the scope of information that can be learned from text for a range of tasks, including sentiment extraction, entity typing and question answering. To this end, we introduce new ideas for how to find effective training data, including crowdsourcing and large-scale naturally occurring weak supervision data. We also describe new computational models, that represent rich social and conversation contexts to tackle these tasks. Together, these advances significantly expand the scope of information that can be incorporated into the next generation of machine reading systems.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Eunsol Choi is a Ph.D candidate at the Paul G. Allen School of Computer Science at the University of Washington. Her research focuses on natural language processing, specifically applying machine learning to recover semantics from text. She completed a B.A. in Computer Science and Mathematics at Cornell University, and is a recipient of the Facebook fellowship.
Host: Xiang Ren
Audiences: Everyone Is Invited
Contact: Assistant to CS chair