Towards generalizable entity-centric clinical coreference resolution.

ABSTRACT:

Objective

This work investigates the problem of clinical coreference resolution in a model that explicitly tracks entities, and aims to measure the performance of that model in both traditional in-domain train/test splits and cross-domain experiments that measure the generalizability of learned models.

Methods

The two methods we compare are a baseline mention-pair coreference system that operates over pairs of mentions with best-first conflict resolution and a mention-synchronous system that incrementally builds coreference chains. We develop new features that incorporate distributional semantics, discourse features, and entity attributes. We use two new coreference datasets with similar annotation guidelines - the THYME colon cancer dataset and the DeepPhe breast cancer dat

SUBMITTER: Miller T 

PROVIDER: S-EPMC5508069 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature