首页> 外文会议>9th International conference on language resources and evaluation >Disambiguating Verbs by Collocation: Corpus Lexicography meets Natural Language Processing
【24h】

Disambiguating Verbs by Collocation: Corpus Lexicography meets Natural Language Processing

机译:通过搭配消除歧义动词:语料库词典与自然语言处理相遇

获取原文

摘要

This paper reports the results of Natural Language Processing (NLP) experiments in semantic parsing, based on a new semantic resource, the Pattern Dictionary of English Verbs (PDEV) (Hanks, 2013). This work is set in the DVC (Disambiguating Verbs by Collocation) project aimed at expanding PDEV to a large scale. This project springs from a long-term collaboration of lexicographers with computer scientists which has given rise to the design and maintenance of specific, adapted, and user-friendly editing and exploration tools. Particular attention is drawn on the use of NLP deep semantic methods to help in data processing. Possible contributions for NLP include pattern disambiguation, the focus of this article. The present article explains how PDEV differs from other lexical resources and describes its structure in detail. It also presents new classification experiments on a subset of 25 verbs. The SVM model obtained a micro-average F1 score of 0.81.
机译:本文报告了基于一种新的语义资源英语动词模式词典(PDEV)的自然语言处理(NLP)实验在语义解析中的结果(Hanks,2013)。这项工作是在旨在大范围扩展PDEV的DVC(通过搭配消除歧义)项目中进行的。该项目源于字典作者与计算机科学家的长期合作,这导致了特定,适应性强且用户友好的编辑和探索工具的设计和维护。特别注意使用NLP深度语义方法来帮助数据处理。对NLP的可能贡献包括模式歧义消除,这是本文的重点。本文介绍了PDEV与其他词汇资源的不同之处,并详细描述了其结构。它还提供了对25个动词子集的新分类实验。 SVM模型的微平均F1得分为0.81。

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