MSM2013 IE Challenge: Annotowatch

In this paper, we describe our approach taken in the MSM2013 IE Challenge, which was aimed at concept extraction from microposts. The goal of the approach was to combine several existing NER tools which use different classification methods and benefit from their combination. Several NER tools have been chosen and individually evaluated on the challenge training set. We observed that some of these tools performed better on different entity types than other tools. In addition, different tools produced diverse results which brought a higher recall when combined than that of the best individual tool. As expected, the precision significantly decreased. The main challenge was in combining annotations extracted by diverse tools. Our approach was to exploit machine-learning methods. We have constructed feature vectors from the annotations yielded by different extraction tools and various text characteristics, and we have used several supervised classifiers to train the classification models. The results showed that several classification models have achieved better results than the best individual extractor.