NLFE to databases have failed in a commercial context, largely because of two reasons. Current approaches to the management of ambiguity by relying on inference over a world model create ungoing customisation requirements. Furthermore the design of NLFEs is subject to constraints which research in CL/ NLP does not address. In particular, standard parsing techniques (including "robust" ones) require complete lexica and cannot be deployed because new data would create a constant need for dictionary update. The SQUIRREL [1] system (SERC Grant GR/E/ 69485) addresses some of these problems: its design reduces customisation effort as words are interpreted without.
