A neural network based Event extraction system for Indian languages Alapan Kuila, Sarath chandra Bussa, and Sudeshna Sarkar Indian institute of Technology kharagpur, India alapan.cse@iitkgp.ac.in, bussasarath2@gmail.com, sudeshna@cseiitkgp.ac.in Abstract. In this paper we have described a neural network based ap- proach for Event extraction(EE) task which aims to discover different types of events along with the event arguments form the text documents written in Indian languages like Hindi, Tamil and English as part of our participation in the task on Event Extraction from Newswires and Social Media Text in Indian Languages at Forum for Information Re- trieval Evaluation (FIRE) in 2018. A neural netork model which is a combination of Convolution neural network(CNN) and Recurrent neural network(RNN) is employed for the Event identification task. In addi- tion to event detection, the system also extracts the event arguments which contain the information related to the events(i.e. when[Time], where[Place], Reason, Casualty, After-effect etc.). Our proposed Event Extraction model achieves f-score of 39.71, 37.42 and 39.91 on Hindi, Tamil and English dataset respectively which shows the overall perfor- mance of Event identification and argument extraction task in these three language domain. Keywords: Event extraction · Convolution neural network(CNN) · Re- current neural network(RNN). 1 Introduction A huge number of news on events, occuring in different corners of the world, are reported each moment in online and printed media. To keep track of those news, it is very important to identify relevant events and extract the spatio-temporal aspects about those events. Understanding events and their descriptions in raw text is the key factor in automatic event extraction which is an important and challenging task in Natural Language Processing(NLP) and Information Extrac- tion(IE). It is also essential in practical applications like news summerization, information retrival and knowledge base construction. Event extraction is an im- portant and challenging task in Information extraction(IE) which aims to detect, from the text, the occurrence of events of specific types, and to discover the argu- ments(event participants or attributes) that are associated with the event. Event Arguments are basically represents the event related information i.e. capturing who does what to whom, how, when and where. For example, – S1: Mild earthquake has been found in Indonesia’s Sulawesi island.