Tagging Complex NEs with MaxEnt Models: Layered Structures Versus Extended Tagset
| 详细信息 | 推荐本文 | |
- 作者：Deyi Xiong ; Hongkui Yu ; Qun Liu
- 刊名：Lecture Notes in Computer Science
- 出版时间：2005
- 出版年：2005
- 期刊代码：99_0302-9743
- 类别：cp
- 卷：3248
- 期：1
- 页码：537-544
- 数据来源：sp
摘要
The paper discusses two policies for recognizing NEs with complex structures by maximum entropy models. One policy is to develop cascaded MaxEnt models at different levels. The other is to design more detailed tags with human knowledge in order to represent complex structures. The experiments on Chinese organization names recognition indicate that layered structures result in more accurate models while extended tags can not lead to positive results as expected. We empirically prove that the {start, continue, end, unique, other} tag set is the best tag set for NE recognition with MaxEnt models.