GATE-a General Architecture for Text Engineering

Much progress has been made in the provision of reusable data resources for Natural Language Engineering, such as grammars, lexicons, thesauruses. Although a number of projects have addressed the provision of reusable algorithmic resources (or 'tools'), takeup of these resources has been relatively slow. This paper describes GATE, a General Architecture for Text Engineering, which is a freely-available system designed to help alleviate the problem. 1 Resource Reuse and Natura l Language Engineering Car designers don't reinvent the wheel each time they plan a new model, but software engineers often find themselves repetitively producing roughly the same piece of software in slightly ditfenmt R)rm. The reasons for this inefficency have been extensively studied, and a number of solutions are now available (Prieto-Diaz and t~h'eeman, 1987; Prieto-Diaz, 1993). Similarly, the Natural Language Engineering (NLE l) community has identified the potential benefits of reducing repetition, and work has been flmded to promote reuse. This work concerns either reusable resources which are primarily data or those which are primarily algorithmic (i.e. processing 'tools', or programs, or code libraries). Successflfl examples of reuse of data resources include: the WordNet thesaurus (Miller el; al., 1993); the Penn Tree Bank (Marcus et al., 1993); the Longmans Dictionary of Contemporary English (Summers, 1995). A large number of papers report results relative to these and other resources, and these successes have spawned a num1See (Boguraev et al., 1995) or (Cunningham et al., 1995) for discussion of the significance of this label. ber of projects with similar directions, one of the latest examples of which being ELRA, tile EuroI)ean Language Resources Association. The reuse of algorithmic resources remains more limited (Gunninghaln et al., 1994). There are a number of reasons for this, including: 1. cultural resistance to reuse, e.g. mistrust of 'foreign' code; 2. integration overheads. In some respects these probleIns are insoluble without general changes in the way NLE research is done researchers will always be reluctant to use poorly-documented or unreliable systems as part of their work, for exmnple. In other respects, solutions are possible. They include: 1. increasing the granularity of the units of reuse, i.e. providing sets of small buildingblocks instead of large, Inonolithic systems; 2. increasing the confidence of researchers in available algorithmic resources by increasing their reuse and the amount of testing and evaluation they are subjected to; 3. separating out, the integration problems that are independent of the type of information being processed and reducing the overhead caused by these problems by providing a software architecture for NLE systems. Our view is that succesful algorithmic reuse in NLE will require the provision of support software for NLE in the form of a general architecture and development environment which is specifically designed for text processing systems. Under EPSRC 2 grant GR/K25267 the NLP group at, the University of Sheffield are developing a system that aims to implement this new approach. The system is called GATE the General Architecture for Text Engineering. ~The Engineering and Physical Science Research Council, UK funding body.