DFKI-LT - Cheap Facts and Counter-Facts

Rui Wang, Chris Callison-Burch
Cheap Facts and Counter-Facts
1 Proceedings of NAACL-HLT 2010 Workshop on Amazon Mechanical Turk, Los Angeles, CA, USA, Association for Computational Linguistics, 6/2010
This paper describes our experiments of using Amazon’s Mechanical Turk to generate (counter-)facts from texts for certain named-entities. We give the human annotators a paragraph of text and a highlighted named-entity. They will write down several (counter-)facts about this named-entity in that context. The analysis of the results is performed by comparing the acquired data with the recognizing textual entailment (RTE) challenge dataset.
Files: BibTeX, AMT2010.pdf