Paper: Outsourcing FrameNet to the Crowd

ACL ID P13-2130
Title Outsourcing FrameNet to the Crowd
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2013
Authors

We present the first attempt to perform full FrameNet annotation with crowdsourcing techniques. We compare two approaches: the first one is the standard annotation methodology of lexical units and frame elements in two steps, while the second is a novel approach aimed at acquiring frames in a bottom-up fashion, starting from frame element annotation. We show that our methodology, relying on a single annotation step and on simplified role defi- nitions, outperforms the standard one both in terms of accuracy and time.