Name
Abstract | ||
|---|---|---|
In this paper, we first create a Cyrillic Mongolian named entity manually annotated corpus. The annotation types contain person names, location names, organization names and other proper names. Then, we use Condition Random Field as classifier and design few categories features of Mongolian, including orthographic feature, morphological feature, gazetteer feature, syllable feature, word clusters feature etc. Experimental results show that all the proposed features improve the overall system performance and stem features improve the most among them. Finally, with a combination of all the features our model obtains the optimal performance. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-50496-4_42 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Cyrillic Mongolian,Named entity recognition,Morphological features,Conditional random field | Conditional random field,Random field,Annotation,Orthographic projection,Computer science,Artificial intelligence,Syllable,Natural language processing,Classifier (linguistics),Named-entity recognition,Proper noun | Conference |
Volume | ISSN | Citations |
10102 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei-Hua Wang | 1 | 42 | 8.06 |
| Fei Long | 2 | 16 | 13.09 |
| Guanglai Gao | 3 | 78 | 24.57 |