In this thesis, we develop, implement and evaluate a strategy for user-guided disambiguation for semantic-enriched search. We use the prototype system Capisco that combines some features of traditional text-based search engines and semantic search engines. Unlike many semantic search approaches that require formulating queries in quite complex semantic languages, the Capisco system is a keyword-based search engine. In this work, we focus on the user-guided disambiguation which helps to capture the users’ information needs. The user-guided disambiguation developed in this thesis explores the semantic meanings for a user-provided keyword and displays these to the users for selection. We explored three different orderings in which the possible keyword meanings may be shown. Using our newly-developed disambiguation interface, the user selects one or several of these meanings from the list offered. The selected semantic meanings are then transferred to the search engine to identify matching documents. This thesis provides an analysis of related work on search interfaces in semantic search, and in methods for semantic disambiguation. We developed the concept of user-guided disambiguation and implemented this concept in a prototype that explored three interface variations. We executed a user study on the three interface alternatives. Finally, we discuss the insights gained during this project, compare our approach to existing literature, and explore possible future work.