Machine knowledge: Creation and curation of comprehensive knowledge bases
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 …
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
Automatic story generation: A survey of approaches
AI Alhussain, AM Azmi - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
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 …
intelligence and psychology intersect to teach computers how to mimic humans' creativity. It …
Hyte: Hyperplane-based temporally aware knowledge graph embedding
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 …
resulting in the development of several KG embedding methods. Relational facts in KG often …
A survey on deep learning event extraction: Approaches and applications
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 …
from massive textual data. With the rapid development of deep learning, EE based on deep …
What is event knowledge graph: A survey
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 …
also an essential kind of knowledge in the world, which trigger the spring up of event-centric …
Joint reasoning for temporal and causal relations
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 …
language understanding task. Because a cause must be before its effect in time, temporal …
The event storyline corpus: A new benchmark for causal and temporal relation extraction
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 …
the temporal and causal relation detection. By developing this dataset, we also introduce a …
[PDF][PDF] Knowledge enhanced event causality identification with mention masking generalizations
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 …
many efforts for this task, existing methods lack the ability to adopt background knowledge …
LearnDA: Learnable knowledge-guided data augmentation for event causality identification
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 …
learning, which are prone to the data lacking problem. Unfortunately, the existing NLP …
KnowDis: Knowledge enhanced data augmentation for event causality detection via distant supervision
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 …
from small hand-labeled corpora. However, hand-labeled training data is expensive to …