Paper: Towards Terascale Semantic Acquisition

ACL ID C04-1111
Title Towards Terascale Semantic Acquisition
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2004

Although vast amounts of textual data are freely available, many NLP algorithms exploit only a minute percentage of it. In this paper, we study the challenges of working at the terascale. We present an algorithm, designed for the terascale, for mining is-a relations that achieves similar performance to a state-of-the-art linguistically-rich method. We fo- cus on the accuracy of these two systems as a func- tion of processing time and corpus size.