Plurality, Negation, and Quantification: Towards Comprehensive Quantifier Scope Disambiguation

Mehdi Manshadi, Daniel Gildea, James F. Allen

Abstract: Recent work on statistical quantifier scope disambiguation (QSD) has improved upon earlier work by scoping an arbitrary number and type of noun phrases. No corpusbased method, however, has yet addressed QSD when incorporating the implicit universal of plurals and/or operators such as negation. In this paper we report early, though promising, results for automatic QSD when handling both phenomena. We also present a general model for learning to build partial orders from a set of pairwise preferences. We give ann logn algorithm for finding a guaranteed approximation of the optimal solution, which works very well in practice. Finally, we significantly improve the performance of the previous model using a rich set of automatically generated features.