Cocoa: Extending a Rule-based System to Tag Disease Attributes in Clinical Records

We extended Cocoa/Peaberry, our (RelAgent) existing rule based entity and event tagger, to tag attributes associated with diseases in clinical records. The boolean attributes of Negation, Uncertainty and Conditional were handled by an extension of the NegEx algorithm. The multi-valued Course and Severity attributes were detected either within the extended disease spans as output by the system, or by event-based annotation using a predicate-argument framework. The anatomical attribute Body Location was marked up by either finding embedded body parts in the extended disease spans or by being colocated close to the disease span. UMLS IDs for anatomical locations were derived by using a small number of morphological lemmas, and by a few rules derived by manual inspection in case of multiple hits. We used the most frequent value in the training data for Subject, Generic, and time-related attributes.