If automatic text processing is to be a useful enterprise, it must be demonstrated that the completeness and accuracy of the information extracted is adequate for the application one has in mind. While it is clear that certain applications require only a minimal level of competence from a system, it is also true that many applications require a very high degree of completeness and accuracy, and an increase in capability in either area is a clear advantage. Therefore we adopt an extremely high standard against which the performance of a text processing system should be measured: it should recover all information that is implicitly or explicitly present in the text, and it should do so without making mistakes.
This standard is far beyond the state of the art. It is an impossibly high standard for human beings, let alone machines. However, progress toward adequate text processing is best served by setting ambitious goals. For this reason we believe that, while it may be necessary in the intermediate term to settle for results that are far short of this ultimate goal, any linguistic theory or system architecture that is adopted should not be demonstrably inconsistent with attaining this objective. However, if one is interested, as we are, in the potentially successful application of these intermediate-term systems to real problems, it is impossible to ignore the question of whether they can be made efficient enough and robust enough for actual applications.