Knowledge-Based News Event Analysis and Forecasting Toolkit

We present a toolkit for knowledge-based news event analysis and forecasting. The toolkit is powered by a Knowledge Graph (KG) of events curated from structured and unstructured sources of event-related knowledge. The toolkit provides functions for 1) mapping ongoing news headlines to concepts in the KG, 2) retrieval, reasoning, and visualization for causal analysis and forecasting, and 3) extraction of causal knowledge from text documents to augment the KG with additional domain knowledge. Each function has a number of implementations using a wide range of state-of-the-art neuro-symbolic techniques. We show how the toolkit enables building a human-in-the-loop explainable solution for event analysis and forecasting.

Authors

• Oktie Hassanzadeh
• Parul Awasthy
• Ken Barker B. Agashe
• Onkar Bhardwaj
• Debarun Bhattacharjya IBM Research
• Mark Feblowitz
• Lee Martie
• Jian Ni
• Kavitha Srinivas IBM Research
• Lucy Yip

Keywords

• Knowledge Representation and Reasoning: Applications
• Knowledge representation and reasoning: General
• Knowledge Representation and Reasoning: Semantic Web
• Natural Language Processing: Applications
• Natural Language Processing: Knowledge Extraction