tailieunhanh - Báo cáo khoa học: "PANEL NATURAL LANGUAGE AND DATABASES"

Natural Language and Databases has been a common panel topic for some years, partly because it has been an active area of work, but more importantly, because it has been widely assumed that database access is a good test environment for language research. I thought the time had come to look again at this assumption, and that it would be useful, for COLING 84, to do this. I therefore invited the members of the Panel to speak to the proposition (developed below) that database query is no longer a good, let alone the best, test environment for language processing. | PANEL NATURAL LANGUAGE AND DATABASES AGAIN Karen Sparck Jones Computer Laboratory University of Cambridge Corn Exchange street Cambridge CB2 3QG England INTRODUCTION Natural Language and Databases has been a common panel topic for some years partly because it has been an active area of work but more importantly because it has been widely assumed that database access is a good test environment for language research. I thought the time had come to look again at this assumption and that it would be useful for COLING 84 to do this. I therefore invited the members of the Panel to speak to the proposition developed below that database query is no longer a good let alone the best test environment for language processing research because it is insufficiently demanding in its linguistic aspects and too idiosyncratically demanding in its non-linguistic ones and to propose better task environments for language understanding research without the disadvantages of database query but with its crucial advantage of an independent evaluation test. DATABASES PROS CONS AND WHAT INSTEAD Database query has a long and honourable history as a vehicle for natural language research. Its value for this purpose was restated for example by Bonnie Webber at IJCAI-83 Webber 1983 . I nevertheless think it is now time to question the value of database query as a continuing vehicle for language research. Database query has two major points in its favour. The task is relatively restricted so success in building a front end does not depend on solving all the problems of language and knowledge processing at once. More importantly the task provides a hard rather than soft test environment for a language processor the processor s performance is independently evaluated via its output formal search query. Natural language research has profited in the past from the restrictions on the database task its limited linguistic functions and world references have allowed concentration on and hence progress in .