1. A method making it possible to manage named entities that are presented in different graphical or syntactic forms and refer to the same entity contained in a database ( 3 ), wherein it comprises at least the following steps: applying a Levenshtein method to said entities E i in the database in order to create a similarity between said entities, defining the measurement of similarity between two entities in the following manner S l ⁡ ( Ei , E j ) = 1 - D ⁡ ( E i , E j ) max ⁡ (  E i  ,  E j  ) with S l being the measurement of similarity between the two entities (E i ,E j ) in the database, D being the Levenshtein distance between the two entities, |E i | respectively |E j | being the number of characters of E i , respectively E j , using the n-grams method to create a similarity S n (E i ,E j ) between the A entities constituting the database, by extracting from the two entities E i and E j the sets N i of the n-grams of E i and the set N j of the n-grams of E j , then defining the number of n-grams |N i | deduced from E i and the number of n-grams |N j | deduced from E j , the similarity between E 1 and E j is then defined by: S n ⁡ ( E i , E j ) =  N i ⋂ N j  min ⁡ (  N i  ,  N j  ) ; using a method of merging the data on said entities in the database in order to construct at least 2 classifications, respectively relating to the n-grams similarity with n greater than or equal to 2, said classifications corresponding to sets of entity partitions P i , wherein the partitions Pi correspond with the classifications of all the entities in the database; finding the consensus partition P c between the M partitions found, using the canonic form entity E c to view the result or else modify the entities present in the database through the canonic form entity.