首页> 外文会议>22nd International Conference on Computational Linguistics >Classifying chart cells for quadratic complexity context-free inference
【24h】

Classifying chart cells for quadratic complexity context-free inference

机译:对图表单元进行分类以进行二次复杂度的无上下文推理

获取原文
获取原文并翻译 | 示例

摘要

In this paper, we consider classifying word positions by whether or not they can either start or end multi-word constituents. This provides a mechanism for "closing" chart cells during context-free inference, which is demonstrated to improve efficiency and accuracy when used to constrain the well-known Charniak parser. Additionally, we present a method for "closing" a sufficient number of chart cells to ensure quadratic worst-case complexity of context-free inference. Empirical results show that this O(n~2) bound can be achieved without impacting parsing accuracy.
机译:在本文中,我们考虑通过单词位置是否可以开始或结束多单词组成对单词位置进行分类。这提供了一种在上下文无关的推理过程中“关闭”图表单元的机制,该机制被证明可以在约束著名的Charniak解析器时提高效率和准确性。此外,我们提出了一种“关闭”足够数量的图表单元以确保上下文无关推论的二次最坏情况复杂度的方法。实验结果表明,可以在不影响解析精度的情况下达到O(n〜2)界。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号