28. A system for automatically extracting relational information from a corpus of text without specifying criteria or patterns for controlling extraction of the relational information, comprising: (a) a memory in which a plurality of machine instructions are stored; (b) a storage in which a corpus of text is stored; (c) an interface for coupling to the storage; and (d) a processor that is coupled to the memory and also coupled to the storage through the interface, the processor executing the machine instructions stored in the memory to carry out a plurality of functions, including: (i) employing a first module that determines a set of linguistic features that are domain independent and which can be used to extract relationships between objects from text; and (ii) employing a second module that uses an extractor and the linguistic features to automatically extract a plurality of tuples from the corpus of text, each tuple including a plurality of objects connected by at least one relationship, wherein the extractor provides the plurality of tuples by tagging at least a portion of words within the corpus of text with each tagged word's most probable part of speech, without parsing the corpus of text and without generating a parse tree.
28. A system for automatically extracting relational information from a corpus of text without specifying criteria or patterns for controlling extraction of the relational information, comprising: (a) a memory in which a plurality of machine instructions are stored; (b) a storage in which a corpus of text is stored; (c) an interface for coupling to the storage; and (d) a processor that is coupled to the memory and also coupled to the storage through the interface, the processor executing the machine instructions stored in the memory to carry out a plurality of functions, including: (i) employing a first module that determines a set of linguistic features that are domain independent and which can be used to extract relationships between objects from text; and (ii) employing a second module that uses an extractor and the linguistic features to automatically extract a plurality of tuples from the corpus of text, each tuple including a plurality of objects connected by at least one relationship, wherein the extractor provides the plurality of tuples by tagging at least a portion of words within the corpus of text with each tagged word's most probable part of speech, without parsing the corpus of text and without generating a parse tree. 30. The system of claim 28 , wherein the machine instructions further cause the processor to automatically learn to rank extracted relationships between objects, by identifying relationships extracted from training data, as being either trustworthy or not trustworthy.