Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Mongolian is an agglutinative language with the complex morphological structures. Building an accurate Named Entity Recognition (NER) system for Mongolian is a challenging and meaningful work.  analyzes the characteristic of Mongolian suffixes using Narrow Non-Break Space and investigates Mongolian NER system under three methods in the Condition Random Field framework. The experiment shows that segmenting each suffix into an individual token achieves the best performance than both without segmenting and using the suffixes as a feature. Our approach obtains an F-measure = 82.71. It is appropriate for the Mongolian large scale vocabulary NER. This research also makes sense to other agglutinative languages NER systems.
['Weihua Wang', 'Feilong Bao', 'Guanglai Gao']
I am writing a research paper on a idea Mongolian Named Entity Recognition using suffixes segmentation
[{"from": "human", "value": "I am writing a research paper on a idea Mongolian Named Entity Recognition using suffixes segmentation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Mongolian is an agglutinative language with the complex morphological structures. Building an accurate Named Entity Recognition (NER) system for Mongolian is a challenging and meaningful work.  analyzes the characteristic of Mongolian suffixes using Narrow Non-Break Space and investigates Mongolian NER system under three methods in the Condition Random Field framework. The experiment shows that segmenting each suffix into an individual token achieves the best performance than both without segmenting and using the suffixes as a feature. Our approach obtains an F-measure = 82.71. It is appropriate for the Mongolian large scale vocabulary NER. This research also makes sense to other agglutinative languages NER systems."}]