The Anaphora-Resolution Module

The anaphora-resolution module used in AGIR is based on the module presented in [Ferrández et al., 1999,Palomar, M., et al., 2001] for the SUPAR system. The algorithm identifies noun phrase (NP) antecedents of personal, demonstrative, reflexive, and zero pronouns in Spanish. It identifies both intrasentential and intersentential antecedents and is applied to the syntactic analysis generated by SUPAR. It also combines different forms of knowledge by distinguishing between constraints and preferences. Whereas constraints are used as combinations of several kinds of knowledge (lexical, morphological, and syntactic), preferences are defined as a combination of heuristic rules extracted from a study of different corpora.

A constraint defines a property that must be satisfied in order for any candidate to be considered as a possible solution of the anaphor. The constraints used in the algorithm are the following: morphological agreement (person, gender, and number) and syntactic conditions on NP-pronoun non-co-reference.

A preference is a characteristic that is not always satisfied by the solution of an anaphor. The application of preferences usually involves the use of heuristic rules in order to obtain a ranked list of candidates. Some examples of preferences used in our system are the following: (a) antecedents that are in the same sentence as the anaphor, (b) antecedents that have been repeated more than once in the text, (c) antecedents that appear before their verbs (i.e., the verb of the clause in which the antecedent appears), (d) antecedents that are proper nouns, (e) antecedents that are an indefinite NP, and so on.

In order to solve pronominal anaphors, they must be first located in the text (anaphora detection) and then resolved (anaphora resolution):

• Anaphora detection. In the algorithm, all the types of anaphors are identified from left to right as they appear in the sentence's slot structure obtained after the partial parsing. To identify each type of pronoun, the information stored in the POS tags has been used. In the particular case of zero pronouns, they have been detected in a previous stage, as previously described.
  
  
• Anaphora resolution. After the anaphor has been detected, the corresponding method, based on constraints and preferences, is applied to solve it. Each type of anaphor has its own set of constraints and preferences, although they all follow the same general algorithm: constraints are applied first, followed by preferences. Constraints discard some of the candidates, whereas preferences simply sort the remaining candidates.