10. A method of disambiguating word senses in at least one natural language text using a graph, comprising: selecting, using a processing unit, a plurality of text units from said at least one natural language text; associating, using the processing unit, at least one word sense with each text unit selected from said at least one natural language text; associating, using the processing unit, the plurality of word senses with a plurality of graph nodes such that each graph node corresponds to one of the word senses that is associated with a text unit selected from said at least one natural language text; determining, using the processing unit, at least one connecting relation between at least two of the plurality of word senses; associating, using the processing unit, said at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes; constructing, using the processing unit, a graph using only the plurality of graph nodes that are associated with one of the text units selected from said at least one natural language text and said at least one graph edge ranking, using the processing unit, the plurality of graph nodes by applying a graph-based ranking algorithm to the graph so that the ranking represents the relative importance, within said at least one natural language text, of the word senses associated with the text units; and selecting, using the processing unit, one word sense for each text unit based on the plurality of rankings.
21. The method of claim 10 , wherein selecting one word sense for each text unit based on the plurality of rankings comprises selecting one word sense for each text unit using at least one of an uninformed and an informed algorithm.