Optimization algorithms for energy-efficient data centers
Hendrik F. Hamann
InterPACK 2013
Two deep parsing components, an English Slot Grammar (ESG) parser and a predicate-argument structure (PAS) builder, provide core linguistic analyses of both the questions and the text content used by IBM Watson™ to find and hypothesize answers. Specifically, these components are fundamental in question analysis, candidate generation, and analysis of passage evidence. As part of the Watson project, ESG was enhanced, and its performance on Jeopardy!™ questions and on established reference data was improved. PAS was built on top of ESG to support higher-level analytics. In this paper, we describe these components and illustrate how they are used in a pattern-based relation extraction component of Watson. We also provide quantitative results of evaluating the component-level performance of ESG parsing. © 1957-2012 IBM.
Hendrik F. Hamann
InterPACK 2013
Daniel M. Bikel, Vittorio Castelli
ACL 2008
Bowen Zhou, Bing Xiang, et al.
SSST 2008
Chidanand Apté, Fred Damerau, et al.
ACM Transactions on Information Systems (TOIS)