7. A method comprising: automatically collecting training data from manually created semantic relations using at least one computerized device, said manually created semantic relations being based on explicit lexical and syntactic information; automatically extracting rules from said training data to produce extracted rules using said computerized device; automatically characterizing existing semantic relations in said training data based on co-occurrence of said extracted rules in said existing semantic relations using said computerized device; automatically constructing semantic relation topics based on said characterizing of said existing semantic relations using said computerized device; grouping instances of said training data into said semantic relation topics to detect new semantic relations using said computerized device, said new semantic relations being based on implicit lexical and syntactic information; receiving at least one input question into said computerized device; identifying ones of said new semantic relations that are present in said input question, to produce question semantic relations corresponding said input question using said computerized device; matching said question semantic relations to data source semantic relations of at least one data source maintained is a separate device external to said computerized device to generate a plurality of candidate answers using said computerized device, said data source semantic relations comprising ones of said new semantic relations present in said data source; calculating an answer score for each of said candidate answers based how closely said question semantic relations match said data source semantic relations using said computerized device; and ranking said candidate answers according to said answer score using said computerized device.
7. A method comprising: automatically collecting training data from manually created semantic relations using at least one computerized device, said manually created semantic relations being based on explicit lexical and syntactic information; automatically extracting rules from said training data to produce extracted rules using said computerized device; automatically characterizing existing semantic relations in said training data based on co-occurrence of said extracted rules in said existing semantic relations using said computerized device; automatically constructing semantic relation topics based on said characterizing of said existing semantic relations using said computerized device; grouping instances of said training data into said semantic relation topics to detect new semantic relations using said computerized device, said new semantic relations being based on implicit lexical and syntactic information; receiving at least one input question into said computerized device; identifying ones of said new semantic relations that are present in said input question, to produce question semantic relations corresponding said input question using said computerized device; matching said question semantic relations to data source semantic relations of at least one data source maintained is a separate device external to said computerized device to generate a plurality of candidate answers using said computerized device, said data source semantic relations comprising ones of said new semantic relations present in said data source; calculating an answer score for each of said candidate answers based how closely said question semantic relations match said data source semantic relations using said computerized device; and ranking said candidate answers according to said answer score using said computerized device. 12. The method according to claim 7 , each of said rules comprising relationships between two logical arguments, and each of said rules having components comprising argument1 type, argument2 type, noun, preposition and verb.