James Hammerton, firstname.lastname@example.org
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.