Pronoun resolution

TLDR: Four examples, including the classic examples of Winograd and Charniak, are presented that demonstrate pronoun resolution within the semantic approach.

Abstract: Two approaches to the problem of pronoun resolution are presented. The first is a naive algorithm that works by traversing the surface parse trees of the sentences of the text in a particular order looking for noun phrases of the correct gender and number. The algorithm is shown to incorporate many, though not all, of the constraints on co-referentiality between a nonreflective pronoun and a possible antecedent, which have been discovered recently by linguists. The algorithm clearly does not work in all cases, but the results of an examination of several hundred examples from published texts show that it performs remarkably well.In the second approach, it is shown how pronoun resolution is handled in a comprehensive system for semantic analysis of English texts. The system consists of four basic semantic operations which work by accessing a data base of 'World knowledge" inferences, which are drawn selectively and in a context-dependent way in response to the operations. The first two operations seek to satisfy the demands made by predicates on the nature of their arguments and to discover the relations between sentences. The third operation - knitting - recognizes and merges redundant expressions. These three operations frequently result in a pronoun reference being resolved as a by-product. The fourth operation seeks to resolve those pronouns not resolved by the first three. It involves a bidirectional search of the text and 'World knowledge" for an appropriate chain of inference and utilizes the efficiency of the naive algorithm.Four examples, including the classic examples of Winograd and Charniak, are presented that demonstrate pronoun resolution within the semantic approach.