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Learning NLP Tasks with SARDSRN

James Hammerton,

We present here a connectionist approach to learning NLP tasks which we hope will cope with large-scale tasks. The approach uses a network architecture known as SARDSRN:

SARDSRN is based on the Simple Recurrent Network (SRN) and incorporates a self-organising map for sequences (known as SARDNET). SARDSRN has been shown to offer better performance than SRNs. To represent the output from the parser we intend to use a connectionist compositional representation of trees indicating the noun-phrases either through bracketing or annotation. In doing this we aim to see whether such techniques can scale-up to large tasks. We hope to present results of an exploratory experiment at the workshop.

This is the abstract of talk in the NP Identification Session of the CoNLL-99 workshop.
Last update: May 22, 2000.