Oren Etzioni

Exploring Markov Logic Networks for Question Answering

2015

Elementary-level science exams pose sig-nificant knowledge acquisition and rea-soning challenges for automatic question answering. We develop a system that rea-sons with knowledge derived from text-books, represented in a subset of first-order logic. Automatic extraction, while …

Parsing Algebraic Word Problems into Equations

2015 · Transactions of the Association for Computational Linguistics

This paper formalizes the problem of solving multi-sentence algebraic word problems as that of generating and scoring equation trees. We use integer linear programming to generate equation trees and score their likelihood by learning local …

Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions

2016 · Proceedings of the AAAI Conference on Artificial Intelligence

What capabilities are required for an AI system to pass standard 4th Grade Science Tests? Previous work has examined the use of Markov Logic Networks (MLNs) to represent the requisite background knowledge and interpret test …

Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

2018 · arXiv (Cornell University)

We present a new question set, text corpus, and baselines assembled to encourage AI research in advanced question answering. Together, these constitute the AI2 Reasoning Challenge (ARC), which requires far more powerful knowledge and reasoning …