Finding My Niche: Becoming a Specialist in Annotation
How I moved from linguistic research into professional data annotation for AI projects.
This section brings together my work on annotation and evaluation: from reflective essays and case studies to reusable schemas, checklists and QA notes. It includes working notes on datasets and evals (schemas, instructions, sampling, rubrics, IAA, error taxonomies, reporting) and shows the decisions and trade-offs behind each project.
How I moved from linguistic research into professional data annotation for AI projects.
How academic conversation analysis relates to day-to-day annotation in AI projects.
How my background in conversation analysis shaped my approach to data annotation, bridging academic methods and industry standards.
Designing and applying a pain-language scheme that integrates conceptual and clinical categories.
Comparing academic and industry approaches to annotating linguistic data.
A small project to prototype an automatic tagger for pain metaphors from concept to first tests.
A hierarchical schema that ties conceptual, clinical and functional categories together.
Quick ideas for light-touch quality review and strategic sampling in annotation projects.
A small personal kit of snippets, templates and prompts I reuse across projects.
Two concise, real-world annotation examples with token-level decisions and guideline rationale.
How I used Cohen’s Kappa and F1 to diagnose disagreement and refine a pain descriptor guideline.
Collaborations, commissions, or a quick question. I reply in English or Spanish.