Word Sense Disambiguation with Very Large Neural Networks Extracted from Machine Readable Dictionaries

In this paper, we describe a means for automatically building very large neural networks (VLNNs) from definition texts in machine-readable dictionaries, and demonstrate the use of these networks for word sense disambiguation. Our method brings together two earlier, independent approaches to word sense disambiguation: the use of machine-readable dictionaries and connectionnist models. The automatic construction of VLNNs enables real-size experiments with neural networks for natural language processing, which in turn provides insight into their behavior and design and can lead to possible improvements.

• Type: Conference
• Year: 1990
• Where: COLING
• Authors: Jean Véronis, Nancy Ide
• Keywords: COLING 1990, COLING 2008, Machine-readable Dictionaries, Neural Networks, Word Sense Disambiguation