Towards Open World Event Knowledge Extraction with Weak Supervision
USC Information Sciences Institute via YouTube
Overview
Syllabus
Intro
What is event extraction?
Application - Intelligence Analysis
Traditional Event Extraction
How to solve the limitations?
Our First Solution: Query-and-Extract
Query and Extract: Type-oriented Binary Decoding
Approach Details - Event Trigger Detection
Approach Details - Event Argument Extraction
Experiments - Supervised Event Extraction
Experiments-Zero-Shot Event Extraction
Event Detection based on Type Specific Prompts
Few-Shot Event Detection
Can the model be continuously updated?
Episodic Memory Prompting
How well the model retrains the capability on old types?
Pros and Cons of Query-and-Extraction Paradigm
Our Second Solution: Self-Training
Why Traditional Self-Training Does Not Work?
Self-Supervised Event Extraction with Gradient Guidance
Self-Training with Gradient Guidance
Evaluation of the Scoring Model
How Effective is the STGG to Event Extraction?
Future Directions: Open-Environment Event Extraction
Taught by
USC Information Sciences Institute