The Semantics of Evidentials in Questions

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Journal of Biomedical Semantics Pub Date : 2020-06-08 DOI:10.1093/jos/ffaa003
Diti Bhadra
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引用次数: 12

Abstract

This paper presents a novel cross-linguistic exploration of the phenomenon of Interrogative Flip at the semantics-pragmatics interfaces. Most previous studies describe an obligatory shift in the anchor of an evidential from the speaker to the addressee in interrogatives, across a diverse set of languages. In this work, we discuss a lesser-studied set of facts, which show that in many languages this shift does not take place. Modeling the contribution of evidentials with ‘judge’-sensitivity in the semantics and with newly refined notions of commitment and sourcehood in an extended dynamic pragmatics framework, the presence or absence of Interrogative Flip is shown to lie in an evidential’s ability to license a commitment update operator $\uparrow $. All attested evidential systems are shown to fall in either the class of $\uparrow $ licensors or not, with apparent exceptions explained across a heterogeneous array of data. A dynamic polar question operator is formulated and its interaction with $\uparrow $ explored. Finally, a novel link between evidentiality and bias is established, by arguing that the lack of the Flip results in biased questions.
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问题中证据的语义
本文在语义-语用界面上对疑问句翻转现象进行了新颖的跨语言探索。大多数先前的研究都描述了在不同语言的疑问句中,证据的锚点从说话人到收件人的强制性转移。在这项工作中,我们讨论了一组较少研究的事实,这些事实表明,在许多语言中,这种转变并没有发生。通过对语义学中具有“判断”敏感性的证据的贡献进行建模,并在扩展的动态语用学框架中对承诺和来源的新概念进行改进,疑问句翻转的存在与否取决于证据授权承诺更新操作符的能力。所有已证明的证据系统都显示属于$ $ uprow $许可人类别,或者不属于此类,在异构数据数组中解释了明显的例外情况。建立了一个动态极坐标问题运算符,并探讨了它与$\ uprow $的交互作用。最后,在证据性和偏见之间建立了一种新的联系,认为缺乏翻转会导致有偏见的问题。
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来源期刊
Journal of Biomedical Semantics
Journal of Biomedical Semantics MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
4.20
自引率
5.30%
发文量
28
审稿时长
30 weeks
期刊介绍: Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas: Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability. Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.
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