Automated, standardized and accurate extraction of relationships within text. Automatic extraction of such relationships/information allows the information to be stored in structured form so that it can be easily and accurately retrieved when needed. Such information can be used to build online search engines for highly specific and accurate information retrieval. Generally, according to the current invention, extracting such information (i.e., relationships within text) from raw text can be accomplished using natural language processing (NLP) and graph theoretic algorithm. Examples of such textual relationships include, but are not limited to, biological relationships between biological terms such as proteins, genes, pathways, diseases and drugs. The current methodology is also able to recognize negative dependences in context, match patterns, and provide a shortest path between related words.
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