1. A method for entity extraction within an electronic document, wherein an entity may be a proper noun; the method comprising: executing by a computer processor a conditional random field algorithm stored on a computer readable medium to generate a conditional random field model; the conditional random field algorithm having an input including one or more training text documents; executing by a computer processor an entity extraction algorithm stored on a computer readable medium to generate an entity extraction model; the entity extraction algorithm having an input including the same one or more training text documents input into the conditional random field algorithm; applying by a computer processor the conditional random field model to at least one electronic document; wherein application of the conditional random field model returns a list of sentences in the at least one electronic document having an entity, and storing the list of sentences with a label indicative of having an entity; applying by a computer processor the entity extraction model to the stored list of sentences with the label indicative of having an entity; wherein application of the entity extraction model returns a list of entities; storing the list of entities on a computer readable medium; extracting from the stored list all sentences relating to a specific entity; wherein the conditional random field model is generated by deconstructing by a computer processor training electronic texts stored on a computer readable into complete sentences and tokens used by the text in each sentence, along with the sequence of sentences; and identifying entities based on either their context within sentences or the tokens used by text in the sentences wherein, given a document containing multiple sentences S:={s 1 , s 2 ,. .. ,s m } and the corresponding entity label for each sentence Entity:={entity 1 , entity 2 ,. .. , entity m }, the conditional random field function defining the probability of the Entity applied to S, Pr(Entity |S), is expressed as: Pr ⁡ ( Entity | S ) = 1 Z S ⁢ exp ⁡ ( ∑ j = 1 K × L ⁢ F j ⁡ ( Concept , S ) ) = 1 Z S ⁢ exp ⁡ ( ∑ i = 1 , k = 1 m , K ⁢ λ k ⁢ f k ⁡ ( y i - 1 , y i , S ) + ∑ i = 1 , l = 1 m , L ⁢ μ l ⁢ g l ⁡ ( y i , S ) ) , ( 1 ) where Z s is a normalization constant f k (y i− 1,y i ,S) is an arbitrary feature function over the group of sentences in a document and positions i and i−1. g l (y i ,S) is a feature function of the state at position i and the document S.