Article
An Architecture of Semantic Information Extraction Tool Text2ALM
Proccedings of the 10th International Scientific and Technical Conference "Open Semantic Technologiesfor Intelligent Systems"
(2020)
Abstract
In this work we design a narrative under-standing tool TEXT2ALM. This tool uses an action language ALM to perform inferences on complex interactions of events described in narratives. The methodology used to implement the TEXT2ALM system was originally outlined by Lierler, Inclezan, and Gelfond via a manual process of converting a narrative to an ALM model. It relies on a conglomeration of resources and techniques from two distinct fields of artificial intelligence, namely, natural language processing and knowledge representation and reasoning. The effectiveness of system TEXT2ALM is measured by its ability to correctly answer questions from the bAbI tasks by Facebook Research in 2015.
Disciplines
Publication Date
February, 2020
Citation Information
Yuliya Lierler and Craig Olson. "An Architecture of Semantic Information Extraction Tool Text2ALM" Proccedings of the 10th International Scientific and Technical Conference "Open Semantic Technologiesfor Intelligent Systems" (2020) Available at: http://works.bepress.com/yuliya_lierler/91/