In using a natural language database interface (NLI) to access the contents of a databese, the user queries may contain terms that do not appear at all in both the NLI lexicon and the database. A friendly NLI should not reject user queries with unknown terms, but should be able to handle them, and should be able to learn new lexical items. Such capability increases the usefulness of the NLI, and allows the NLI to more cover the domain of the underlying database. Therefore, a technique to handle unknown terms is decisive in designing a friendly NLI. In this work, we discuss a method that would allow a NLI to identify the meanings of unknown database field values, and terms that are exceeding the conceptual coverage of the database, in the user queries, by engaging the user in clarification dialogues based on a database-domain hierarchy. It will be shown that the method enables the NLI lexicon to learn new lexical items at run time while the clarification dialogues, and it may provide the necessary information for generating informative answers to some particular failing user queries. Moreover, the method is an efficient means to handle queries with insufficience contextual cues. The examples throughout this work are drawn from FIFA 90, an experimental NLI to a soccer database.