An Improved Redundancy Elimination Algorithm for Underspecified Representations 
 We present an efficient algorithm for the redundancy elimination problem : Given an underspecified semantic representation (USR) of a scope ambiguity , compute an USR with fewer mutually equivalent readings . The algorithm operates on underspecified chart representations which are derived from dominance graphs ; it can be applied to the USRs computed by large-scale grammars . We evaluate the algorithm on a corpus , and show that it reduces the degree of ambiguity significantly while taking negligible runtime. 