9. A method for identifying semantically relevant documents, comprising: maintaining an index comprising semantic index key terms from one or more documents; obtaining a query and identifying semantic key terms of the query, wherein each of the query key terms are associated with information comprising use of the word and a grammatical role of the word; and looking up the each of the query key terms and variants of the query key terms in the index based on the information; identifying one or more of the documents in the index as possible relevant candidates based on the look up; generating a potential match candidate set by filtering the possible relevant candidates; identifying at least one of the documents that match the query by comparing a semantic representation for each filtered potential match candidate in the set with a semantic representation for the query, wherein each of the semantic representation for the query and the semantic representation for each potential match candidate in the set comprises one or more semantic substructures, comprising: aligning the substructures for the query semantic representation and one or more of the semantic representations for the potential match candidates; and assigning a score to the one or more potential match candidates by identifying shared substructures with the query semantic representation.
16. A method according to claim 9 , further comprising: adjusting the score for the one or more potential match candidates based on a distance of relationships for the substructures, synonyms, and hypernyms.