Plumeria
Labeled text data by identifying central claims, emotional tone, and topic categories in user-generated content. Applied detailed instruction sets and maintained high accuracy while meeting daily task quotas.
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I am an experienced AI training data contributor with a strong background in text annotation, content moderation, and LLM evaluation. I have worked on diverse projects involving claim identification, tone analysis, search relevance, and prompt response rating in both English and Indonesian. My attention to detail, ability to follow complex guidelines, and commitment to high-quality outputs make me a reliable asset in data labeling and natural language processing (NLP) tasks. I have contributed to projects such as Fireweed and Plumeria, gaining hands-on experience with tools and platforms used in AI training workflows. With over 20 hours of weekly availability and a professional background in structured data work, I am confident in my ability to support high-volume annotation projects effectively.
Labeled text data by identifying central claims, emotional tone, and topic categories in user-generated content. Applied detailed instruction sets and maintained high accuracy while meeting daily task quotas.
Assessed the quality and relevance of AI-generated responses based on multiple criteria such as factuality, helpfulness, and coherence. Worked with English and Indonesian prompts. Followed strict guidelines to ensure consistent and accurate evaluations.
Bachelor's Degree, Chemical Engineering
Diploma, Chemical Engineering
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