arXiv cs.CL· Tirana Noor Fatyanosa, Ummu Ditya Erliana, Mahendra Data, Muhammad Nurwegiono, Eleazar Tadeo Eman, Alham Fikri Aji·· 13 小时前AI 评分18
IndoNutriQA：印尼语临床营养问答基准发布
IndoNutriQA: An Indonesian Clinical Nutrition Question Answering Benchmark
AI 导读
研究团队构建了 IndoNutriQA，一个由专家整理的印尼语临床营养问答基准，包含 911 个问答对，全部基于真实临床营养报告。数据集覆盖遵循营养护理流程（NCP）的 8 种标准化问题类型，答案由营养师撰写的自由文本构成，专家验证发现 6-10% 的参考答案存在争议。
正文 · 原文
Abstract:Clinical Question Answering (QA) underpins Clinical Intelligent Decision Support Systems, but progress is severely limited for low-resource languages such as Indonesian by the absence of public domain-specific data. We introduce IndoNutriQA, an expert-curated Indonesian clinical QA benchmark of 911 question-answer pairs built from real clinical-nutrition reports. Rather than a large-scale training corpus, it is positioned as a high-quality evaluation resource: every pair is grounded in a clinically relevant context, enriched with structured metadata (anthropometric assessment, medical diagnosis, document provenance, chunk segmentation). Eight standardised question types following the Nutrition Care Process (NCP), including the Problem, Etiology, Sign and Symptom (PES) diagnosis statement, are answered for every report, which was written by a graduate-level dietetic intern, by one of three nutritionists. Answers are free-form clinical prose rather than extractive spans, and an expert validation study finds 6-10% of reference answers contestable. The dataset supports generative, extractive and retrieval-augmented QA as well as zero- and few-shot LLM evaluation. We report fine-tuned baselines (IndoBERT variants, mT5, RAG) with 5-fold cross-validation, learning curves and bootstrap 95% confidence intervals, and benchmark eight contemporary LLMs zero- and five-shot. We further calibrate our LLM-as-judge rubric against three expert raters (one RD, two nutritionists), finding it human-comparable on factuality and completeness but unreliable on clinical safety, and a human error analysis shows it misses unsupported content that the raters identify. IndoNutriQA is released to foster research in Indonesian clinical NLP and nutritional decision support.
| Comments: | 26 pages (9 pages main text, plus limitations, ethics, references and appendix), 5 figures, 18 tables. Under review at EACL. Data and code: this https URL |
| Subjects: | Computation and Language (cs.CL) |
| ACM classes: | I.2.7; J.3 |
| Cite as: | arXiv:2610.31256 [cs.CL] |
| (or arXiv:2610.31256v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.31256 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Tirana Noor Fatyanosa [view email]
[v1]
Thu, 22 Oct 2026 13:34:29 UTC (150 KB)
来源：arXiv cs.CL · arxiv.org