A comprehensive gold standard for the Enron organizational hierarchy

Authors:
Apoorv Agarwal;Adinoyi Omuya;Aaron Harnly;Owen Rambow
Affiliations:
Columbia University, New York, NY;Columbia University, New York, NY;Wireless Generation Inc., Brooklyn, NY;Columbia University, New York, NY
Venue:
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
Year:
2012

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Abstract

Many researchers have attempted to predict the Enron corporate hierarchy from the data. This work, however, has been hampered by a lack of data. We present a new, large, and freely available gold-standard hierarchy. Using our new gold standard, we show that a simple lower bound for social network-based systems outperforms an upper bound on the approach taken by current NLP systems.