Disambiguating prepositional phrase attachment sites with sense information captured in contextualized distributional data

被引：0

作者：

Greenberg, Clayton ^{[1
]}

机构：

[1] Univ Saarland, Dept Computat Linguist & Phonet, Saarbrucken, Germany

来源：

52ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: STUDENT RESEARCH WORKSHOP (ACL 2014) | 2014年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This work presents a supervised prepositional phrase (PP) attachment disambiguation system that uses contextualized distributional information as the distance metric for a nearest-neighbor classifier. Contextualized word vectors constructed from the GigaWord Corpus provide a method for implicit Word Sense Disambiguation (WSD), whose reliability helps this system outperform baselines and achieve comparable results to those of systems with full WSD modules. This suggests that targeted WSD methods are preferable to ignoring sense information and also to implementing WSD as an independent module in a pipeline.

引用

页码：71 / 77

页数：7