AUTOMATIC INDUCTION OF RULES FOR TEXT SIMPLIFICATION

Long and complicated sentences pose various problems to many state-of- the-art natural language technologies. We have been exploring methods to automatically transform such sentences in order to make them simple r. These methods involve the use of a rule-based system, driven by the syntax of the text in the domain of interest. Hand-crafting rules for every domain is time-consuming and impractical. The paper describes a n algorithm and an implementation by which generalized rules for simpl ification are automatically induced from annotated training material u sing a novel partial parsing technique which combines constituent stru cture and dependency information. The algorithm described in the paper employs example-based generalizations on linguistically motivated str uctures. (C) 1997 Elsevier Science B.V.