12. A system for generating a language processing engine using high-coverage training data, the system comprising: an interface configured to receive a set of potential training data snippets, each potential training data snippet comprising one or more n-grams; an n-gram scorer configured to, for each selected snippet of two or more of the potential training data snippets, compute a snippet score for the selected snippet by: identifying one or more n-grams of the selected snippet as unseen n-grams; obtaining a frequency value the identified unseen n-grams; computing a length value of the selected snippet; and computing the snippet score for the selected snippet based on a comparison of the obtained frequency values and the length value of the selected snippet; and an n-gram sorter configured to sort the set of potential training data snippets, as sorted snippets, based on the computed snippet scores, and wherein the n-gram sorter configured to store the potential training data snippets in a memory; wherein the language processing engine is created using multiple of the potential training data snippets based on their order in sorted set of potential training data snippets to perform automated language processing functions.
12. A system for generating a language processing engine using high-coverage training data, the system comprising: an interface configured to receive a set of potential training data snippets, each potential training data snippet comprising one or more n-grams; an n-gram scorer configured to, for each selected snippet of two or more of the potential training data snippets, compute a snippet score for the selected snippet by: identifying one or more n-grams of the selected snippet as unseen n-grams; obtaining a frequency value the identified unseen n-grams; computing a length value of the selected snippet; and computing the snippet score for the selected snippet based on a comparison of the obtained frequency values and the length value of the selected snippet; and an n-gram sorter configured to sort the set of potential training data snippets, as sorted snippets, based on the computed snippet scores, and wherein the n-gram sorter configured to store the potential training data snippets in a memory; wherein the language processing engine is created using multiple of the potential training data snippets based on their order in sorted set of potential training data snippets to perform automated language processing functions. 15. The system of claim 12 , wherein the length value of the selected snippet is based on a count of words in the selected snippet.