基于溯因解释的学习提高了解析的准确性和效率

O. Streiter
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摘要

自然语言解析必须准确、快速。基于解释的学习(EBL)是一种加速解析的技术。然而,EBL的准确性经常下降。本文表明,这种准确性损失不是由于EBL框架本身,而是由于演绎解析。溯因EBL允许扩展解析器的演绎闭包。提出了一种基于溯因法的中文解析器。实验表明,该方法在精度和效率上均有提高
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Abductive Explanation-based Learning Improves Parsing Accuracy and Efficiency
Natural language parsing has to be accurate and quick. Explanation-based Learning (EBL) is a technique to speed-up parsing. The accuracy however often declines with EBL. The paper shows that this accuracy loss is not due to the EBL framework as such, but to deductive parsing. Abductive EBL allows extending the deductive closure of the parser. We present a Chinese parser based on abduction. Experiments show improvements in accuracy and efficiency.1
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