Developing classification-based named entity recognizers (NER) for Sambalpuri and Odia applying support vector machines (SVM) - Behera, Pitambar; Muzaffar, Sharmin (Nepalese Linguistics, 2018)
This paper demonstrates the development of named Entity Recognizers (NER) applying Support Vector Machines (SVM) for Sambalpuri and Odia. The Sambalpuri corpus amounts to 112k word tokens out of which 5,887 are named entities. On the contrary, 250k ILCI corpus has been applied for Odia out of which 18,447 tokens are named entities. The former accurately recognizes 96.72% whereas the latter provides 98.10% accuracy.