2,000+ Free Courses with Certificates: Coding, AI, SQL, and More
Lead AI-Native Products with Microsoft's Agentic AI Program
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
Explore two insightful lectures from the Fall 2019 NLP Seminar featuring Nathan Schneider from Georgetown University and Vivek Srikumar from the University of Utah. Delve into the complexities of preposition semantics and their importance in linguistic meaning representations with Schneider's talk on "The Ins and Outs of Preposition Semantics." Learn about challenges in corpus annotation and automatic disambiguation, and discover ongoing work on semantic markers across multiple languages. Then, shift focus to Srikumar's presentation on "What Logic can Teach Neural Networks," examining innovative approaches to training neural networks using declarative rules and logic. Gain insights into reducing dependence on labeled data and improving model consistency in text understanding tasks. Originally recorded on October 9, 2019, this 1 hour 37 minute seminar offers closed captions and is part of the Paul G. Allen School's NLP seminar series.
Syllabus
Fall 2019 NLP Seminar: Nathan Schneider (Georgetown University) & Vivek Srikumar (Univ. of Utah)
Taught by
Paul G. Allen School