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arXiv · 1902.01541

The Referential Reader: A Recurrent Entity Network for Anaphora Resolution

Fei Liu·Luke Zettlemoyer·Jacob Eisenstein
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Abstract

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 fixed-length 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.

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Fei Liu, Luke Zettlemoyer, Jacob Eisenstein. 2019-07-09. The Referential Reader: A Recurrent Entity Network for Anaphora Resolution. https://arxiv.org/abs/1902.01541

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