Computing Implicit Entities and Events with GETARUNS

R. Delmonte
{"title":"Computing Implicit Entities and Events with GETARUNS","authors":"R. Delmonte","doi":"10.5220/0002171600230035","DOIUrl":null,"url":null,"abstract":"In this paper we will focus on the notion of “implicit” or lexically unexpressed linguistic elements that are nonetheless necessary for a complete semantic interpretation of a text. We referred to “entities” and “events” because the recovery of the implicit material may affect all the modules of a system for semantic processing, from the grammatically guided components to the inferential and reasoning ones. Reference to the system GETARUNS offers one possible implementation of the algorithms and procedures needed to cope with the problem and allows to deal with all the spectrum of phenomena. The paper will address at first the following three types of “implicit” entities and events: the grammatical ones, as suggested by a linguistic theories like LFG or similar generative theories; the semantic ones suggested in the FrameNet project, i.e. CNI, DNI, INI; the pragmatic ones: here we will present a theory and an implementation for the recovery of implicit entities and events of (non-) standard implicatures. In particular we will show how the use of commonsense knowledge may fruitfully contribute in finding relevant implied meanings. Last Implicit Entity only touched on, though for lack of space, by the paper is the Subject of Point of View which is computed by Semantic Informational Structure and contributes the intended entity from whose point of view is expressed a given subjective statement.","PeriodicalId":378427,"journal":{"name":"International Workshop on Natural Language Processing and Cognitive Science","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Natural Language Processing and Cognitive Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0002171600230035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In this paper we will focus on the notion of “implicit” or lexically unexpressed linguistic elements that are nonetheless necessary for a complete semantic interpretation of a text. We referred to “entities” and “events” because the recovery of the implicit material may affect all the modules of a system for semantic processing, from the grammatically guided components to the inferential and reasoning ones. Reference to the system GETARUNS offers one possible implementation of the algorithms and procedures needed to cope with the problem and allows to deal with all the spectrum of phenomena. The paper will address at first the following three types of “implicit” entities and events: the grammatical ones, as suggested by a linguistic theories like LFG or similar generative theories; the semantic ones suggested in the FrameNet project, i.e. CNI, DNI, INI; the pragmatic ones: here we will present a theory and an implementation for the recovery of implicit entities and events of (non-) standard implicatures. In particular we will show how the use of commonsense knowledge may fruitfully contribute in finding relevant implied meanings. Last Implicit Entity only touched on, though for lack of space, by the paper is the Subject of Point of View which is computed by Semantic Informational Structure and contributes the intended entity from whose point of view is expressed a given subjective statement.
使用getarun计算隐式实体和事件
在本文中,我们将重点关注“隐含”或词汇上未表达的语言元素的概念,这些元素对于文本的完整语义解释是必要的。我们提到了“实体”和“事件”,因为隐式材料的恢复可能会影响语义处理系统的所有模块,从语法引导组件到推理和推理组件。参考系统GETARUNS提供了处理该问题所需的算法和过程的一种可能实现,并允许处理各种现象。本文将首先讨论以下三种类型的“隐含”实体和事件:语法上的实体和事件,如语言学理论如LFG或类似的生成理论所建议的;框架网项目建议的语义类,即CNI、DNI、INI;实用主义方面:在这里,我们将提出一种理论和实现,用于恢复(非)标准含义的隐含实体和事件。特别是,我们将展示如何使用常识性知识在寻找相关的隐含意义方面可能会有丰硕的贡献。由于篇幅有限,本文最后只涉及到的隐含实体是由语义信息结构计算出来的观点主体,它提供了一个意图实体,从这个实体的观点来表达一个给定的主观陈述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信