Coreference analysis in clinical notes: a multi-pass sieve with alternate anaphora resolution modules.

ABSTRACT:

Objective

This paper describes the coreference resolution system submitted by Mayo Clinic for the 2011 i2b2/VA/Cincinnati shared task Track 1C. The goal of the task was to construct a system that links the markables corresponding to the same entity.

Materials and methods

The task organizers provided progress notes and discharge summaries that were annotated with the markables of treatment, problem, test, person, and pronoun. We used a multi-pass sieve algorithm that applies deterministic rules in the order of preciseness and simultaneously gathers information about the entities in the documents. Our system, MedCoref, also uses a state-of-the-art machine learning framework as an alternative to the final, rule-based pronoun resolution sieve.

Results

The best system that

SUBMITTER: Jonnalagadda SR 

PROVIDER: S-EPMC3422831 | biostudies-literature | 2012 Sep-Oct

REPOSITORIES: biostudies-literature