13. The computer-based method of claim 12 further comprising: reorganizing a relational lexical database into an automaton; and organizing all entries in said database to be related to each other by word senses, sense content, and semantic relations and their sense content.
12. A computer-implemented method of semantic information retrieval based on a semantic dictionary augmented with explicit rules that enable machine learning and deep contextual understanding comprising: curating in real-time and interactively semantic expressions taken from a networked database; configuring a gloss vector engine operable to generate semantic gloss vectors for data mining by unsupervised machine learning; configuring a deconstruction engine operable to identify well-formed sentences; configuring a data discovery engine operable to identify indirect communicating links; configuring a collocation engine operable to identify compound nouns; configuring a disambiguation engine operable to assign appropriate nouns given context; configuring a generic noun disambiguation engine operable to identify context shifts produced by use of generic or common nouns; configuring a pronoun disambiguation engine operable to link common nouns to proper nouns; configuring a data evaluation engine operable to identify well-formed sentences containing information of maximal semantic value; configuring a retrieval engine operable to return information of the highest semantic value for a given search term; and configuring a context targeting engine operable to display in context the specific sentence in the source article showing the query results wherein one or more users can dynamically obtain responses to queries of multiple search terms across bodies of corpus.