Benchmarking Mi-AR: Malay anaphora resolution

This paper discusses benchmarking a new approach that uses the maximum entropy model and Random Forest classifier for pronominal anaphora resolution in the Malay language. Given the specific characteristics of the Malay language, such as gender-neutral pronouns, we pursued a specific two-phase methodology: (1) conducting analyses to scrutinize the features of Malay anaphors, and (2) designing, implementing, and evaluating a pronominal resolution system based on the analysis results. The approach achieved a 0.84 F-measure in testing with 9,779 tokens (i.e. 50 news and 50 non-news articles), and the results of our experiment and comparison study show that the presented approach significantly outperforms the current state-of-the-art Malay anaphora resolution systems.