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[Seminar] Towards Deeper Natural Language Understanding

Friday, March 12, 2021

11:00 am - 12:00 pm

Location

Online (link TBA)

Abstract

Extracting meaning from text is key to natural language understanding and many end-user applications. Natural language is notoriously ambiguous, and humans intuitively understand many nuances in meaning as well as implicit inferences. In this talk I will present models that enable intelligent systems to better understand natural language.

First, I will present our work on extracting implicit positive meaning hidden in sentences containing negation. I will discuss approaches to pinpoint the few elements that are actually negated and strategies to generate plausible affirmative interpretations. Second, I will present our work on extracting temporally-anchored spatial knowledge indicating where somebody is located over time.

About the Speaker

Eduardo Blanco is an Associate Professor in the Department of Computer Science and Engineering at University of North Texas. He conducts research primarily in natural language processing with a focus on computational semantics, including semantic relation extraction and intricate linguistic phenomena such as negation, modality, and uncertainty. He is interested in both fundamental research and applications in the social sciences, medicine, and robotics among others. His work is supported by the National Science Foundation, the National Geospatial-Intelligence Agency, the Patient-Centered Outcomes Research Institute, and generous gifts from industry. Blanco is a recipient of the Bloomberg Data Science Research Grant and the National Science Foundation CAREER Award.

Eduardo Blanco
Location
Online via MS Teams