יום שישי, 31 ביולי 2026 LIVE
AI־INFO

כתבה arXiv cs.AI ·

Frontier LLM-based agents can overcome the ontology curation bottleneck for natural phenotypes

תקציר מקורי באנגליתarXiv:2605.28965v2 Announce Type: replace Abstract: Linking free-text phenotype descriptions to ontology terms, typically referred to as phenotype annotation, is essential for the cross-study integration of comparative morphological data. This labor intensive process has heavily relied on highly trained human experts, which makes it challenging to scale and thus a key bottleneck. Dahdul et al. (2018) established a Gold Standard (GS) of Entity-Quality (EQ) annotations across seven phylogenetic studies and used it to evaluate three human curators and the Semantic CharaParser NLP tool with ontology-based semantic similarity metrics; they reported that machine-human consistency was significantly lower than inter-curator (human-human) consistency. Here we revisit that benchmark with five fronti
קרא במקור המקורי