Quality Assessment of Large Scale Knowledge Resources

This paper presents an empirical evaluation of the quality of publicly available large-scale knowledge resources. The study includes a wide range of manually and automatically derived large-scale knowledge resources. In order to establish a fair and neutral comparison, the quality of each knowledge resource is indirectly evaluated using the same method on a Word Sense Disambiguation task. The evaluation framework selected has been the Senseval-3 English Lexical Sample Task. The study empirically demonstrates that automatically acquired knowledge resources surpass both in terms of precision and recall the knowledge resources derived manually, and that the combination of the knowledge contained in these resources is very close to the most frequent sense classifier. As far as we know, this is the first time that such a quality assessment has been performed showing a clear picture of the current state-of-the-art of publicly available wide coverage semantic resources.

• Type: Conference
• Year: 2006
• Where: EMNLP
• Authors: Montse Cuadros, German Rigau
• Keywords: Available Large-scale Knowledge, EMNLP 2006, EMNLP 2007, Knowledge Resources, Large-scale Knowledge Resources