A corpus driven approach applying the "frame semantic" method for modeling functional status terminology.

Stud Health Technol Inform

Division of Medical Informatics Research, Department of Health Sciences Research, Harwick 826, Mayo Clinic, 200 SW First Street, Rochester, MN 55905, USA.

Published: June 2005

AI Article Synopsis

  • Researchers utilized the "frame semantic" method, informed by the Berkeley "FrameNet" Project, to enhance functional-status terminology development.
  • They extracted descriptive sentences from a corpus of clinical questionnaire assessments, annotating syntactic components to identify their semantic roles.
  • The study highlights how these "semantic frames" and "frame elements" can aid in developing semantic models for functional-status terminology and improve machine recognition in clinical narratives.

Article Abstract

In an effort to unearth semantic models that could prove fruitful to functional-status terminology development we applied the "frame semantic" method, derived from the linguistic theory of thematic roles currently exemplified in the Berkeley "FrameNet" Project. Full descriptive sentences with functional-status conceptual meaning were derived from structured content within a corpus of questionnaire assessment instruments commonly used in clinical practice for functional-status assessment. Syntactic components in those sentences were delineated through manual annotation and mark-up. The annotated syntactic constituents were tagged as frame elements according to their semantic role within the context of the derived functional-status expression. Through this process generalizable "semantic frames" were elaborated with recurring "frame elements". The "frame semantic" method as an approach to rendering semantic models for functional-status terminology development and its use as a basis for machine recognition of functional status data in clinical narratives are discussed.

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