7. A computer program product, comprising: a computer-readable storage medium; and a computer-readable program code stored in the computer-readable storage medium, the computer-readable program code containing instructions that are carried out by a central processing unit (CPU) of a computer system to implement a method of ranking candidate answers to a natural language question, the method comprising the steps of: the computer system identifying first contextual information about a user of a mobile device, the first contextual information including (1) interests of the user based on historical usage of the mobile device by the user to run applications on the mobile device, visit websites via a browser provided by the mobile device, display textual articles on the mobile devices, enter terms into a search engine via the mobile device, and capture multimedia content, (2) a geographic location of the user provided by a global positioning system (GPS) coupled to the mobile device, (3) data specifying characteristics of an environment in proximity to the user, the characteristics of the environment being detected and measured by a first sensor coupled to the mobile device, and (4) data specifying a bodily function of the user, the bodily function being detected and measured by a second sensor coupled to the mobile device; based on the first contextual information, the computer system determining a prioritization of definitions of terms; based on the first contextual information and the prioritization of the definitions of the terms, the computer system generating a lexicon of the terms; using a forecaster that employs mobile-based time series manipulation and pattern recognition and based on (1) the historical usage of the mobile device by the user to run the applications on the mobile device, visit the websites via the browser provided by the mobile device, display the textual articles on the mobile devices, enter the terms into the search engine via the mobile device, and capture the multimedia content, (2) the geographic location of the user provided by the GPS coupled to the mobile device, (3) the data specifying characteristics of the environment in proximity to the user, and (4) the data specifying the bodily function of the user, the computer system forecasting second contextual information that indicates future behavior of the user; based on the forecasted second contextual information, the computer system performing word sense disambiguation of the terms in the lexicon and adjusting the prioritization of the definitions of the terms in the lexicon; based on the word sense disambiguation of the terms in the lexicon and the adjusted prioritization of the definitions of the terms, the computer system modifying the candidate answers to the natural language question; and based in part on the adjusted prioritization of the definitions of the terms in the lexicon, the modified candidate answers, and the forecasted second contextual information, the computer system ranking the modified candidate answers to the natural language question, the highest ranked modified candidate answer being more likely to be a correct answer to the natural language question than the other candidate answers.
7. A computer program product, comprising: a computer-readable storage medium; and a computer-readable program code stored in the computer-readable storage medium, the computer-readable program code containing instructions that are carried out by a central processing unit (CPU) of a computer system to implement a method of ranking candidate answers to a natural language question, the method comprising the steps of: the computer system identifying first contextual information about a user of a mobile device, the first contextual information including (1) interests of the user based on historical usage of the mobile device by the user to run applications on the mobile device, visit websites via a browser provided by the mobile device, display textual articles on the mobile devices, enter terms into a search engine via the mobile device, and capture multimedia content, (2) a geographic location of the user provided by a global positioning system (GPS) coupled to the mobile device, (3) data specifying characteristics of an environment in proximity to the user, the characteristics of the environment being detected and measured by a first sensor coupled to the mobile device, and (4) data specifying a bodily function of the user, the bodily function being detected and measured by a second sensor coupled to the mobile device; based on the first contextual information, the computer system determining a prioritization of definitions of terms; based on the first contextual information and the prioritization of the definitions of the terms, the computer system generating a lexicon of the terms; using a forecaster that employs mobile-based time series manipulation and pattern recognition and based on (1) the historical usage of the mobile device by the user to run the applications on the mobile device, visit the websites via the browser provided by the mobile device, display the textual articles on the mobile devices, enter the terms into the search engine via the mobile device, and capture the multimedia content, (2) the geographic location of the user provided by the GPS coupled to the mobile device, (3) the data specifying characteristics of the environment in proximity to the user, and (4) the data specifying the bodily function of the user, the computer system forecasting second contextual information that indicates future behavior of the user; based on the forecasted second contextual information, the computer system performing word sense disambiguation of the terms in the lexicon and adjusting the prioritization of the definitions of the terms in the lexicon; based on the word sense disambiguation of the terms in the lexicon and the adjusted prioritization of the definitions of the terms, the computer system modifying the candidate answers to the natural language question; and based in part on the adjusted prioritization of the definitions of the terms in the lexicon, the modified candidate answers, and the forecasted second contextual information, the computer system ranking the modified candidate answers to the natural language question, the highest ranked modified candidate answer being more likely to be a correct answer to the natural language question than the other candidate answers. 8. The computer program product of claim 7 , wherein the method further comprises the computer system adjusting weights of a machine learning ensemble based on the forecasted second contextual information, wherein the machine learning ensemble includes (1) logistic regression phases and routes, (2) dimensions of evidence refinement, (3) probability density functions, classification techniques, and regression techniques, (4) natural language processing systems, and (5) a data retrieval system.