1. A named-entity detection apparatus comprising: a candidate-named-entity extraction module detecting a candidate-named-entity based on an initial learning example and feature information regarding morphemes constituting an inputted sentence, the candidate-named-entity extraction module providing a tagged sentence including the detected candidate-named-entity, wherein the candidate-named-entity extraction module is hardware module; a storage module storing information regarding a named-entity dictionary and a rule; and a learning-example-regeneration module determining whether the candidate-named-entity included in the provided sentence is a valid named-entity, based on the named-entity dictionary and the rule, and providing the sentence as a learning example, based on a determination result, so that a probability of named-entity candidate detection is gradually updated, wherein the candidate-named-entity extraction module determines a class of each morpheme by using a learning model based on the feature information, and provides a tagged sentence by adding determined class information as a tag, wherein the learning example provided by the learning-example-regeneration module is reflected in the learning module as a negative example when the rule is violated, wherein the probability of detecting the named-entity of the candidate-named-entity extraction module is gradually updated in the learning module when the learning example is a negative example, 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.
1. A named-entity detection apparatus comprising: a candidate-named-entity extraction module detecting a candidate-named-entity based on an initial learning example and feature information regarding morphemes constituting an inputted sentence, the candidate-named-entity extraction module providing a tagged sentence including the detected candidate-named-entity, wherein the candidate-named-entity extraction module is hardware module; a storage module storing information regarding a named-entity dictionary and a rule; and a learning-example-regeneration module determining whether the candidate-named-entity included in the provided sentence is a valid named-entity, based on the named-entity dictionary and the rule, and providing the sentence as a learning example, based on a determination result, so that a probability of named-entity candidate detection is gradually updated, wherein the candidate-named-entity extraction module determines a class of each morpheme by using a learning model based on the feature information, and provides a tagged sentence by adding determined class information as a tag, wherein the learning example provided by the learning-example-regeneration module is reflected in the learning module as a negative example when the rule is violated, wherein the probability of detecting the named-entity of the candidate-named-entity extraction module is gradually updated in the learning module when the learning example is a negative example, 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. 3. The named-entity detection apparatus of claim 1 , wherein the named-entity dictionary comprises unambiguous named-entities.