Ontopopulis is an unsupervised system for learning semantic dictionaries from unannotated text corpora. It takes a small seed set of terms for each semantic class and extracts contextual features to score and rank new term candidates. Evaluation shows it can learn new terms with 70% or higher accuracy, outperforming supervised approaches. The system has been applied to tasks like event extraction, summarization, and opinion mining in several languages.