16. The method of claim 15 , wherein the rule is an error inspection rule using at least one selected from the group consisting of a meaning string pattern and an excluded word list.
15. A named-entity detection method comprising: extracting a candidate named-entity, which is a potential named-entity, from a user utterance including a sentence using an initial learning example and feature information regarding morphemes constituting the sentence by a candidate-named-entity extraction module, wherein the candidate-named-entity extraction module is a hardware module; determining whether a candidate named-entity matches an item registered in a dictionary by a learning-example-regeneration module; verifying the candidate named-entity as a named-entity when the candidate named-entity matches an item registered in the dictionary and providing the candidate named-entity as a new positive learning example to a learning model by the learning-example-regeneration module; and determining whether the candidate named-entity violates a rule when the candidate named-entity does not match an item registered in the dictionary, providing the candidate named-entity as a new negative learning example to the learning model when the candidate violates a rule, updating the probability of detecting the named-entity of the learning-example-regeneration module gradually when the new negative learning example violates the rule, and verifying the candidate named-entity as a named-entity when the candidate named-entity does not violate any rule, wherein the feature information comprises a word feature, a part-of-speech feature, a concept feature, an adjacent verb feature, and an adjacent verb concept feature, and wherein the concept feature comprises ontological concept information of a current morpheme as well as three morphemes before and after the current morpheme.