The Referential Reader: A Recurrent Entity Network for Anaphora Resolution
Fei Liu, Luke Zettlemoyer, Jacob Eisenstein · 2019
We present a new architecture for storing and accessing entity mentions during online text processing.While reading the text, entity references are identified, and may be stored by either updating or overwriting a cell in a fixedlength memory.The update operation implies coreference with the other mentions that are stored in the same cell; the overwrite operation causes these mentions to be forgotten.By encoding the memory operations as differentiable gates, it is possible to train the model end-to-end, using both a supervised anaphora resolution objective as well as a supplementary language modeling objective.Evaluation on a dataset of pronoun-name anaphora demonstrates strong performance with purely incremental text processing.