Feature Based Approach to Named Entity Recognition and Linking for Tweets (original) (raw)

In this paper, we describe our approach for Named Entity rEcognition and Linking Challenge (NEEL) at the #Micro-posts2016. The task is to automatically recognize entities and their types from English microposts, and link them to corresponding DBpedia 2015 entries. If the resources do not exist, we use NIL identifiers instead. The task is unique as twitter data is informal in nature with non-conformational spellings, random contractions and various other noises. For this task, we developed our system using a hybrid model. We have used various existing named entity recognition (NER) systems and combined them with our classifier to improve the results.

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