  We classify and review current approaches to software infrastructure for
research, development and delivery of NLP systems. The task is motivated by a
discussion of current trends in the field of NLP and Language Engineering. We
describe a system called GATE (a General Architecture for Text Engineering)
that provides a software infrastructure on top of which heterogeneous NLP
processing modules may be evaluated and refined individually, or may be
combined into larger application systems. GATE aims to support both researchers
and developers working on component technologies (e.g. parsing, tagging,
morphological analysis) and those working on developing end-user applications
(e.g. information extraction, text summarisation, document generation, machine
translation, and second language learning). GATE promotes reuse of component
technology, permits specialisation and collaboration in large-scale projects,
and allows for the comparison and evaluation of alternative technologies. The
first release of GATE is now available - see
http://www.dcs.shef.ac.uk/research/groups/nlp/gate/
