Equipping machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

Computational generation of stories is a subfield of computational creativity where artificial
intelligence and psychology intersect to teach computers how to mimic humans' creativity. It …

Abstract Knowledge Graph (KG) embedding has emerged as an active area of research
resulting in the development of several KG embedding methods. Relational facts in KG often …

Event extraction (EE) is a crucial research task for promptly apprehending event information
from massive textual data. With the rapid development of deep learning, EE based on deep …

Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are
also an essential kind of knowledge in the world, which trigger the spring up of event-centric …

Understanding temporal and causal relations between events is a fundamental natural
language understanding task. Because a cause must be before its effect in time, temporal …

This paper reports on the Event StoryLine Corpus (ESC) v1. 0, a new benchmark dataset for
the temporal and causal relation detection. By developing this dataset, we also introduce a …

Identifying causal relations of events is a crucial language understanding task. Despite
many efforts for this task, existing methods lack the ability to adopt background knowledge …

Modern models for event causality identification (ECI) are mainly based on supervised
learning, which are prone to the data lacking problem. Unfortunately, the existing NLP …

Modern models of event causality detection (ECD) are mainly based on supervised learning
from small hand-labeled corpora. However, hand-labeled training data is expensive to …