Term variation is an important issue in various applications of natural language processing (NLP) such as machine translation, information retrieval and text indexing. In this paper, the authors describe an ‘Abductive Terminological Database’ (ATDB) aiming to detect translations of terms and their variants in bilingual texts. They describe abduction as the process to infer specific term translation templates from multiple resources which have been induced from a bilingual text. They show that precision and recall of the ATDB increase when using more resources and when the resources interfere in a less restricted way. Finally, the authors discuss a way to feed back evaluation values into the induced resources thus allowing for weighted abduction which further enhances the precision of the tool.