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Text analytics systems often rely heavily on detecting and linking entity mentions in documents to knowledge bases for downstream applications such as sentiment analysis, question answering and recommender systems. A major challenge for this task is to be able to accurately detect entities in new languages with limited labeled resources. In this paper we present an accurate and lightweight 1 multilingual named entity recognition (NER) and linking (NEL) system. The contributions of this paperdoi:10.1145/3018661.3018724 dblp:conf/wsdm/PappuBMST17 fatcat:brp5m4y6g5bjli7snvq6pzinna