Learning Fine-Grained Knowledge about Contingent Relations between Everyday Events

Understand

Much of the user-generated content on social media is provided by ordinary people telling stories about their daily lives.

• We develop and test a novel method for learning fine-grained common-sense knowledge from these stories about contingent (causal and conditional) relationships between everyday events.
• This type of knowledge is useful for text and story understanding, information extraction, question answering, and text summarization.
• We test and compare different methods for learning contingency relation, and compare what is learned from topic-sorted story collections vs.