Disambiguating Entities Referred by Web Endpoints using Tree Ensembles

This paper describes system details and results of team “EOF” from the University of Melbourne in the shared task of ALTA 2016, which addresses the use of cross document coreference resolution to determine whether two URLs refer to the same underlying entity. In our submission, we develop a two stage system which first identifies the underlying entity for a given URL using entity-level features by ranking the entity mentions present in the crawled text with the help of logistic regression. This is followed by disambiguating entities present in the given pair of URLs using a tree ensemble model to classify if both URLs refer to the same underlying entity. Our system achieved a final F1-score of 86.02% on the private leaderboard1, which is the best score among all the participating systems.