Hi, I've been playing around with the opennlp wrappers and will probably make use of the entity detection, but I was wondering about the sentence and token detection.
It seems that a model (statistical) based approach may be overkill and more of a pain to correct errors in. I was wondering if there's any reason not to use a rule based sentence/token detector that then feeds the opennlp pos and entity model based annotators? Any thought are welcome. - Jonathan
