1. A method for automatically extracting and mining relations and related entities from unstructured text, comprising: Receiving a query specifying a main entity; and Extracting, using a computer processing system, from unstructured text relations and related entities related to the main entity specified in the query, the extracting further comprising: Searching and selecting in the unstructured text, documents containing the main entity; Attaching to each word of the selected documents, at least one tag, each tag being of a different type; extracting relations and related entities by applying patterns to the tagged documents, wherein the patterns are induced from unstructured text, the inducing comprising: attaching to each word of an unstructured text, at least one tag of a different type; defining at least one template, each template being based on a sequence of tags; and Generating from each template, at least one pattern, each pattern specifying a role for each tag in the template; Extracting from the selected documents features characterizing each entity and relation; and building a graph based on the extracted features, whose nodes represent the entities related to the specified main entity and whose edges represent the relations between the entities, wherein building a graph based on the extracted features further comprises expanding the graph based on distances between nodes, the expanding further comprising selecting at least one expanded entity, close to the main entity, and extracting from the unstructured text, relations and related entities related to each expanded entity; wherein extracting features characterizing each relation from the selected documents further comprises associating each relation with a relation class, a relation strength, and temporal information, and wherein building the graph further comprises indicating on the graph which of the entities are related at a given time based on the temporal information for each relation.
1. A method for automatically extracting and mining relations and related entities from unstructured text, comprising: Receiving a query specifying a main entity; and Extracting, using a computer processing system, from unstructured text relations and related entities related to the main entity specified in the query, the extracting further comprising: Searching and selecting in the unstructured text, documents containing the main entity; Attaching to each word of the selected documents, at least one tag, each tag being of a different type; extracting relations and related entities by applying patterns to the tagged documents, wherein the patterns are induced from unstructured text, the inducing comprising: attaching to each word of an unstructured text, at least one tag of a different type; defining at least one template, each template being based on a sequence of tags; and Generating from each template, at least one pattern, each pattern specifying a role for each tag in the template; Extracting from the selected documents features characterizing each entity and relation; and building a graph based on the extracted features, whose nodes represent the entities related to the specified main entity and whose edges represent the relations between the entities, wherein building a graph based on the extracted features further comprises expanding the graph based on distances between nodes, the expanding further comprising selecting at least one expanded entity, close to the main entity, and extracting from the unstructured text, relations and related entities related to each expanded entity; wherein extracting features characterizing each relation from the selected documents further comprises associating each relation with a relation class, a relation strength, and temporal information, and wherein building the graph further comprises indicating on the graph which of the entities are related at a given time based on the temporal information for each relation. 2. The method according to claim 1 , further comprising: manipulating the graph in order to gain more insight into information it contains.