ChemSpot 2.0 is a set of tools for named entity recognition and classification of chemicals in natural language texts, including trivial names, abbreviations, molecular formulas and IUPAC entities. Since the different classes of relevant entities have rather different naming characteristics, ChemSpot uses a combined approach of employing a Conditional Random Field and a dictionary, as well as pattern-based recognition, a classifier model and several methods for consolidating all annotations. ChemSpot also performs named entity normalization by assigning identifiers from numerous chemical databases. It achieves an F1 measure of 79.0% on the SCAI corpus.