AMRITA_CEN @ FIRE 2015: Extracting Entities for Social Media Texts in Indian Languages

This contemporary work is done as a slice of the shared task on Entity Extraction from Social Media Text Indian Languages in Forum for Information Retrieval and Evaluation (FIRE2015). Nowadays people are extensively using social media platforms like Face book, Twitter, etc, to exchange their thoughts. The twitter messages are growing rapidly and their style and short nature present a new challenge in language technology field. This extensive amount of textual data is also increases the interest in Information Extraction (IE) on such textual data. Named entity extraction is one of the essential tasks in Information Extraction, aims to extract and classify entities from text. The performance of the present standard language processing tools is severely affected on Tweet messages. Hence, different improvised and nonimprovised algorithms are necessary for extracting these entities from the informal text. This paper deals with the extracting the Named Entities from twitter messages of four Indian Languages. The extraction of the Named entity relies mainly on the domain specific features and conventional features. A well known supervised algorithm, Support Vector Machine (SVM) is used to extracting the entities. CCS Concepts • Theory of computation~Support vector machines • Computing methodologies~Natural language processing • Information systems~Information extraction • Human-centered computing~Social tagging systems