AAAI Publications, Workshops at the Twenty-Fourth AAAI Conference on Artificial Intelligence

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Machine Reading: A "Killer App" for Statistical Relational AI
Hoifung Poon, Pedro Domingos

Last modified: 2010-07-07


Machine reading aims to automatically extract knowledge from text. It is a long-standing goal of AI and holds the promise of revolutionizing Web search and other fields. In this paper, we analyze the core challenges of machine reading and show that statistical relational AI is particularly well suited to address these challenges. We then propose a unifying approach to machine reading in which statistical relational AI plays a central role. Finally, we demonstrate the promise of this approach by presenting OntoUSP, an end-to-end machine reading system that builds on recent advances in statistical relational AI and greatly outperforms state-of-the-art systems in a task of extracting knowledge from biomedical abstracts and answering questions.


statistical relational AI, machine reading, unsupervised semantic parsing, probabilistic ontology induction, Markov logic

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