17. A computer-implemented method of automatic rule generation, comprising: (a) generating a rule from a sample; (b) generating, by a computing device, a relaxed rule from the rule and, if the relaxed rule matches a stored rule, returning the relaxed rule as an appropriate extraction rule; (c) generating a reverse index of a corpus to determine a superset of documents from the corpus that satisfy the relaxed rule as compared to a set of documents that satisfy the rule; (d) generating text segments by applying the relaxed rule from the superset of documents; (e) generating modified text segments from the text segments and the relaxed rule; (f) performing a candidate generation process on the modified text segments; (g) if the candidate generation process generates no candidates, performing again (b) using a further relaxed rule as the relaxed rule; (h) if the candidate generation process generates a candidate from the modified text segments, performing: (i) receiving an evaluation from a user for the candidate; (j) providing the candidate as an additional sample; and (k) performing again (a) using the sample and the additional sample to generate another rule to use as the rule, wherein the evaluation from the user is used in generating the rule.
18. The computer-implemented method of claim 17 , wherein the sample is one of a plurality of samples, wherein the plurality of samples includes at least one positive sample, and wherein the rule is generated from the plurality of samples.