1. A method comprising: training a plurality of sentence annotation models, via a computer, on a corpus of annotated sentences, wherein each sentence annotation model of the plurality of sentence annotation models uses a different sentence annotation algorithm; with the computer, applying each of the plurality of sentence annotation models to a first sentence not included in the corpus of annotated sentences, to generate a plurality of sentence annotations, each of the plurality of sentence annotations resulting from application of one of the plurality of sentence annotation models to the first sentence, each of the plurality of sentence annotations comprising a parse tree that includes a set of tags, labels, and/or connections for words of the first sentence; and comparing the plurality of sentence annotations to select a best sentence annotation for the first sentence from among the plurality of sentence annotations, wherein the comparing comprises: sending the parse tree resulting from application of each of the plurality of sentence annotation models to a rover; determining in the rover a best set of tags, labels, and/or connections for the first sentence based on a comparison of the sets of tags, labels, and/or connections resulting from application of the plurality of sentence annotation models; annotating words of the first sentence using the best set of tags, labels, and/or connections; and tagging the best set of tags, labels, and/or connections as reliable or unreliable.