11. A method, implemented by a computing device, comprising: providing a chunking specification; providing one or more part-of-speech-tagged corpora; chunking the one or more corpora, with a processor, in accordance with the chunking specification, the chunking comprising: chunking nouns, noun-verbs, pronouns, noun-adjectives, noun morphemes, and named entities, either single or as the head in a modifier-head structure with a modifier comprising a noun, a numerical phrase, or an adjective phrase, as noun chunks; chunking verbs, verb-particle structures in which the particle comprises an oriented verb or an auxiliary, and modifier-verb structures in which the modifier comprises an adverbial phrase or an auxiliary verb, in verb chunks; refining the chunking specification through iterative chunking consistency feedback with a training corpus, wherein one or more groups of identical or similar sections of text from different parts of the training corpus that have been chunked differently from each other are compared, and for one or more of the groups, the chunking of one of the identical or similar sections of text is selected to replace the chunking of the other identical or similar sections of text within the group; automatically calculating, with a processor, a consistency ratio for the chunking of the training corpus; comparing the calculated consistency ratio with a chunk consistency threshold, wherein refining the chunking specification is continued at least until the calculated consistency ratio meets the chunk consistency threshold; incorporating the refined chunking specification in a chunking utility that also comprises a plurality of definitions of chunk types and a set of chunking rules; receiving an input; assigning chunk types to portions of the input based at least in part on the chunking utility comprising the refined chunking specification; and providing an output comprising the portions of the input with the assigned chunk types.
11. A method, implemented by a computing device, comprising: providing a chunking specification; providing one or more part-of-speech-tagged corpora; chunking the one or more corpora, with a processor, in accordance with the chunking specification, the chunking comprising: chunking nouns, noun-verbs, pronouns, noun-adjectives, noun morphemes, and named entities, either single or as the head in a modifier-head structure with a modifier comprising a noun, a numerical phrase, or an adjective phrase, as noun chunks; chunking verbs, verb-particle structures in which the particle comprises an oriented verb or an auxiliary, and modifier-verb structures in which the modifier comprises an adverbial phrase or an auxiliary verb, in verb chunks; refining the chunking specification through iterative chunking consistency feedback with a training corpus, wherein one or more groups of identical or similar sections of text from different parts of the training corpus that have been chunked differently from each other are compared, and for one or more of the groups, the chunking of one of the identical or similar sections of text is selected to replace the chunking of the other identical or similar sections of text within the group; automatically calculating, with a processor, a consistency ratio for the chunking of the training corpus; comparing the calculated consistency ratio with a chunk consistency threshold, wherein refining the chunking specification is continued at least until the calculated consistency ratio meets the chunk consistency threshold; incorporating the refined chunking specification in a chunking utility that also comprises a plurality of definitions of chunk types and a set of chunking rules; receiving an input; assigning chunk types to portions of the input based at least in part on the chunking utility comprising the refined chunking specification; and providing an output comprising the portions of the input with the assigned chunk types. 13. The method of claim 11 , wherein the input is received in a format other than text, and the method further comprises converting the input into a text format, prior to the assigning the chunk types to the portions of the input.