Abstract:
Named entity recognition (NER) can be introduced as one of the fundamental tasks
in natural language processing. The type and boundary are the two components of a
named entity (NE) in text. There are various research have been applied to detect the
NE types and boundary as two separate tasks and there is no existing mechanism to
consider both of these tasks together. NER in social media analysis considering
expressions, disputes etc. can also be considered as something which carries a huge
demand. Furthermore, most of these mechanisms have been followed considering
English as the testing language corpus and there is an overwhelming demand for
such a system which supports for multiple languages including Sinhala. So, the
intention is to implement a system for NE boundary detection for Sinhala language
considering religious unhealthy statements in social media. Detecting both NE
boundary and NE type as an aggregate mechanism will tune up the accuracy and
performance of NE linking to knowledge bases. The approach will be determined by
some of the aspects such as identifying the existing mechanisms of NE type detection
and NE boundary detection, identifying the complexity indexes, matrices and
relationships of religious unhealthy statements in Sinhala, identifying the novelty in
implementing NE boundary detection considering NE types of religious unhealthy
statements and finally enhancing NE linking considering NE boundary detection.
The ultimate target is to implement a prototype which out forms the stateof-the-art
existing baselines.
