A web survey on the use of active learning to support annotation of text data

As supervised machine learning methods for addressing tasks in natural language process-ing (NLP) prove increasingly viable, the fo-cus of attention is naturally shifted towards the creation of training data. The manual annota-tion of corpora is a tedious and time consum-ing process. To obtain high-quality annotated data constitutes a bottleneck in machine learn-ing for NLP today. Active learning is one way of easing the burden of annotation. This pa-per presents a first probe into the NLP research community concerning the nature of the anno-tation projects undertaken in general, and the use of active learning as annotation support in particular.