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Modeling Actions and State Changes for a Machine Reading Comprehension Dataset

Abstract Artificial general intelligence consists of many components, one of which is Natural Language Understanding (NLU). One of the applications of NLU is Reading Comprehension where it is expected that a system understand all aspects of a text. Further, understanding natural procedure-describing text that deals with existence of entities and effects of actions on these entities while doing reasoning and inference at the same time is a particularly difficult task. A recent natural language dataset by the Allen Institute of Artificial Intelligence, ProPara, attempted to address the challenges to determine entity existence and entity tracking in natural text.

As part of this work, an attempt is made to address the ProPara challenge. The Knowledge... (more)
Created Date 2019
Contributor Bhattacharjee, Aurgho (Author) / Baral, Chitta (Advisor) / Yang, Yezhou (Committee member) / Anwar, Saadat (Committee member) / Arizona State University (Publisher)
Subject Computer science / inductive logic programming / machine comprehension / machine reading comprehension / modeling actions / modeling states / natural language processing
Type Masters Thesis
Extent 94 pages
Language English
Note Masters Thesis Computer Science 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis