Information Extraction Tool Text2Alm: From Narratives to Action Language System DescriptionsProceedings of the 35th International Conference on Logic Programming (ICLP) (2019)
In this work we design a narrative understanding tool Text2Alm. System Text2Alm uses an action language ALM to perform inferences on complex interactions of events described in narratives. The methodology used to implement the Text2Alm was originally outlined by Lierler et al. 2017 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 published by Facebook Research in 2015. This tool matched or exceeded the performance of state-of-the-art machine learning methods in six of the seven tested tasks. We also illustrate that the Text2Alm approach generalizes to a broader spectrum of narratives.
- Information Extraction,
- Question Answering
Publication DateSeptember, 2019
Citation InformationCraig Olson and Yuliya Lierler. "Information Extraction Tool Text2Alm: From Narratives to Action Language System Descriptions" Proceedings of the 35th International Conference on Logic Programming (ICLP) (2019)
Available at: http://works.bepress.com/yuliya_lierler/86/