1. A system that uses a combination of semantic and statistical processing of input or data content, comprising: a system including a computer having a processor and memory that receives an input in the form of a user-entered search query, a set of text retrieved by an automated robot process, web page, electronic document, or some other form of input; a semantically-enhanced statistical lookup data, which is created by analysis of a plurality of documents on various topics, to determine sufficient and necessary keyphrases, wherein a keyphrase is considered sufficient for a particular topic when if that keyphrase is found in the input, the input is likely to be in that topic, and a keyphrase is considered necessary for a particular topic when, if that keyphrase is found in the input, the input is both very likely to be in that topic, and very unlikely to be in any other topic; a semantically-enhanced comparison logic which uses the information in the semantically-enhanced statistical lookup data to analyze the input, compare search words in the input with keyphrases, determine an appropriate topic, and generate an appropriate output; and wherein keyphrases have an entropy associated therewith, wherein keyphrases that are sufficient for a particular topic have a relatively lower entropy than keyphrases that are sufficient for several topics, and a relatively higher entropy than keyphrases that are necessary for the particular topic; and wherein for a particular topic, the set of necessary keyphrases are a subset of sufficient keyphrases for that topic.
3. The system of claim 1 , wherein the semantically-enhanced statistical lookup data includes a plurality of entries, including for each of a plurality of topics a plurality of keyphrases associated with that topic, together with an indication or factor as to whether that keyphrase is sufficient and whether that keyphrase is necessary, and optionally an indication or factor as to the keyphrase's entropy.