The adverb ”then” is among the most frequent English temporal adverbs, being also capable of filling a variety of semantic roles. The identification of anaphoric usages of ”then” is important for temporal expression resolution, while the temporal relationship usage is important for event ordering. Given that previous work has not tackled the identification and temporal resolution of anaphoric ”then”, this paper presents a machine learning approach for setting apart anaphoric usages and a rule-based normaliser that resolves it with respect to an antecedent. The performance of the two modules is evaluated. The present paper also describes the construction of an annotated corpus and the subsequent derivation of training data required by the machine learning module.