Towards Open World Event Knowledge Extraction with Weak Supervision
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a comprehensive lecture on open world event knowledge extraction using weak supervision techniques. Delve into the challenges of current research paradigms and discover innovative approaches to reduce reliance on human effort in event extraction. Learn about the Query-and-Extract paradigm, which leverages event schemas as natural language queries to extract candidate events from text. Examine the self-training with gradient guidance framework, designed to improve event extraction models using pseudo labels from unlabeled data. Gain insights into supervised, few-shot, and zero-shot extraction settings, as well as strategies for incrementally updating models with new event types. Understand the application of these techniques in intelligence analysis and their potential for advancing natural language processing in open world scenarios.