Efficient named entity annotation through pre-empting

Linguistic annotation is time-consuming and expensive. One common annotation task is to mark entities - such as names of people, places and organisations - in text. In a document, many segments of text often contain no entities at all. We show that these segments are worth skipping, and demonstrate a technique for reducing the amount of entity-less text examined by annotators, which we call "preempting". This technique is evaluated in a crowdsourcing scenario, where it provides downstream performance improvements for the same size corpus.