Named Entity Recognition for Code Mixing in Indian Languages using Hybrid Approach
Automating the process of Named Entity Recognition has received a lot of attention over past few years in Social Media Text. Named Entities are real world objects such as Person, Organization, Product, Location. Identifying these entities in social media text is an important challenging task due the informal nature of text present on social media. One such challenge that is faced in recognizing named entities in Indian Social Media Text is Code Mixing. Code Mixing is usage of more than one language in a sentence. Being a multilingual country, people of India tend to know more than one language, which in turn results in the code mixing of text while expressing their opinions. This paper describes the proposed approach for shared task CMEE IL (Code Mix Entity Extraction in Indian Language) FIRE 2016. Proposed algorithm uses a hybrid approach of a dictionary cum supervised classification approach for identifying entities in Code Mix Text of Indian Languages such as HindiEnglish and Tamil English. CCS Concepts *Computing methodologies Natural language processing; Information extraction; Language resources; Machine learning;
FIRE