To the best of our knowledge, the dataset presented in this work includes the large majority of high-quality labeled taste data publicly available today and may serve as a useful resource for future work on small molecule taste prediction. Nonetheless, the scarcity of data on umami compounds makes this a particularly challenging taste category also for FART. Progress is already underway to build increasingly powerful chemical language models that could be fine-tuned using a similar approach as outlined here. However, we believe meaningful breakthroughs in taste prediction will not come from methodological advancements alone but requires the collection of larger, well-curated, and accessible datasets. Automated, experimental taste classification remains a large unmet need in the field of food chemistry today.