29. A method for labeling, the method comprising: identifying, by a computer system comprising one or more processors, a plurality of patterns in a plurality of documents, the plurality of patterns not covered by a set of validated contextual rules; (a) selecting, by the computer system, a batch of documents of the plurality of documents according to a frequency of usage of patterns included in the batch of documents of the plurality of documents, where the frequency of usage is for the plurality of documents; (b) submitting, by the computer system, the batch of documents of the plurality of documents to a crowdsourcing community for labeling; (c) receiving, by the computer system, labels for the batch of documents of the plurality of documents; (d) generating, by the computer system, proposed contextual rules based on labeled documents of the plurality of documents by: identifying one or more patterns in the labeled documents and a usage frequency for the one or more patterns identified; selecting a top N patterns of the one or more patterns having highest usage frequencies; if a label of the labeled documents has a high correspondence to a pattern of the top N patterns of the one or more patterns, generating a proposed contextual rule relating the pattern of the top N patterns of the one or more patterns to the label; and otherwise, generating a proposed contextual rule that includes the pattern of the top N patterns of the one or more patterns but no related label; (e) submitting, by the computer system, the proposed contextual rules to an analyst community for validation; (f) receiving, by the computer system, validation of a portion of the proposed contextual rules; and (g) adding the portion validated of the proposed contextual rules to the set of validated contextual rules.
29. A method for labeling, the method comprising: identifying, by a computer system comprising one or more processors, a plurality of patterns in a plurality of documents, the plurality of patterns not covered by a set of validated contextual rules; (a) selecting, by the computer system, a batch of documents of the plurality of documents according to a frequency of usage of patterns included in the batch of documents of the plurality of documents, where the frequency of usage is for the plurality of documents; (b) submitting, by the computer system, the batch of documents of the plurality of documents to a crowdsourcing community for labeling; (c) receiving, by the computer system, labels for the batch of documents of the plurality of documents; (d) generating, by the computer system, proposed contextual rules based on labeled documents of the plurality of documents by: identifying one or more patterns in the labeled documents and a usage frequency for the one or more patterns identified; selecting a top N patterns of the one or more patterns having highest usage frequencies; if a label of the labeled documents has a high correspondence to a pattern of the top N patterns of the one or more patterns, generating a proposed contextual rule relating the pattern of the top N patterns of the one or more patterns to the label; and otherwise, generating a proposed contextual rule that includes the pattern of the top N patterns of the one or more patterns but no related label; (e) submitting, by the computer system, the proposed contextual rules to an analyst community for validation; (f) receiving, by the computer system, validation of a portion of the proposed contextual rules; and (g) adding the portion validated of the proposed contextual rules to the set of validated contextual rules. 30. The method of claim 29 , wherein generating, by the computer system, the proposed contextual rules based on the labeled documents of the plurality of documents comprises: identifying one or more patterns in the labeled documents and a usage frequency for the one or more patterns identified; selecting a top N patterns of the one or more patterns having highest usage frequencies; if a label of the labeled documents has a high correspondence to a pattern of the top N patterns of the one or more patterns, generating a proposed contextual rule relating the pattern of the top N patterns of the one or more patterns to the label; and otherwise, generating a proposed contextual rule that includes the pattern of the top N patterns of the one or more patterns but no related label.