Paper: Knowing What to Believe (when you already know something)

ACL ID C10-1099
Title Knowing What to Believe (when you already know something)
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

Although much work in NLP has focused on simply determining what a document means, we also must know whether or not to believe it. Fact-finding algorithms at- tempt to identify the “truth” among com- peting claims in a corpus, but fail to take advantage of the user’s prior knowl- edge and presume that truth itself is uni- versal and objective rather than subjec- tive. We introduce a framework for incor- porating prior knowledge into any fact- finding algorithm, expressing both gen- eral “common-sense” reasoning and spe- cific facts already known to the user as first-order logic and translating this into a tractable linear program. As our results show, this approach scales well to even large problems, both reducing error and allowing the system to determine truth re- spective to t...