Applying Genetic Algorithms to Pronoun Resolution

Introduction Many pronoun resolution algorithms work by calculating the most salient candidate antecedent. However, many factors affect salience, for example being the syntactic subject or the most frequently mentioned item, and these factors must be combined into an aggregate salience score. One technique is to assign weights for each factor representing the amount by which that factor impacts the overall salience, and the candidate antecedent which accumulates the most weight is selected. Previous authors assigned weights heuristically (cf. Mitkov 1998). By using a genetic algorithm to select the weights, our program beats baseline techniques, and can be customized for each language domain.1