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This paper presents the experiments carried out by us at Jadavpur Universityas part of the participation in FIRE 2015 task: Entity Extraction from SocialMedia Text - Indian Languages (ESM-IL). The tool that we have developed for thetask is based on Trigram Hidden Markov Model that utilizes information likegazetteer list, POS tag and some other word level features to enhance theobservation probabilities of the known tokens as well as unknown tokens. Wesubmitted runs for English only. A statistical HMM (Hidden Markov Models) basedmodel has been used to implement our system. The system has been trained andtested on the datasets released for FIRE 2015 task: Entity Extraction fromSocial Media Text - Indian Languages (ESM-IL). Our system is the best performerfor English language and it obtains precision, recall and F-measures of 61.96,39.46 and 48.21 respectively.

A Hidden Markov Model Based System for Entity Extraction from Social Media English Text at FIRE 2015