Year: 2026
Type: conference-paper
Abstract: We present an annotation schema for Haitian Creole medical translation that makes clinical risk and sociolinguistic variation explicit while remaining lightweight enough for small expert teams.The schema includes binary fields for overall acceptability, severity of potential misunderstanding, and foreign-influence cues, along with conditional error tags aligned with Multidimensional Quality Metrics (MQM), commonly used in the medical domain, for interoperability.Through three rounds of annotation and adjudication we achieve stable inter-annotator agreement and release a gold dataset of 152 EN→HC medical sentence pairs.A simple classifier-labeller baseline demonstrates that acceptability and severity are reliably learnable under data scarcity, while foreign-influence judgments remain limited by prevalence.These results show that clinically oriented, variety-sensitive annotation can both support immediate screening of patient-facing translations and provide reward-ready signals for future preference-based MT and LLM finetuning.
Source: Linguistic Annotation Workshop
Institutions: University of Miami, University of Alabama
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7166837113