Towards Harnessing Memory Networks for Coreference Resolution

Joe Cheri, Pushpak Bhattacharyya


Abstract
Coreference resolution task demands comprehending a discourse, especially for anaphoric mentions which require semantic information for resolving antecedents. We investigate into how memory networks can be helpful for coreference resolution when posed as question answering problem. The comprehension capability of memory networks assists coreference resolution, particularly for the mentions that require semantic and context information. We experiment memory networks for coreference resolution, with 4 synthetic datasets generated for coreference resolution with varying difficulty levels. Our system’s performance is compared with a traditional coreference resolution system to show why memory network can be promising for coreference resolution.
Anthology ID:
W17-2605
Volume:
Proceedings of the 2nd Workshop on Representation Learning for NLP
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venues:
RepL4NLP | WS
SIG:
SIGREP
Publisher:
Association for Computational Linguistics
Note:
Pages:
37–42
Language:
URL:
https://www.aclweb.org/anthology/W17-2605
DOI:
10.18653/v1/W17-2605
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-2605.pdf