Comparing Degree-Based and Argumentative Analyses of Even

Pola Osher, Yael Greenberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper adds to the discussion of the nature of the scale on which even operates: on which dimension is such a scale based? The paper suggests a comparative analysis of two recent accounts, namely the degree-based approach proposed by Y. Greenberg and the argumentative approach proposed by G. Winterstein. Following the former, even operates on a scale based on a gradable property. We claim that the argumentative approach of Winterstein may be interpreted as operating on the interval argumentative scale, which we suggest in this paper. The comparative analysis of the two approaches is conducted on three different levels: the level of data that they both account for (Sect. 3.2), on the structural level (Sect. 3.3), and on the functional level (3.4). At the end of the paper (cf. Sect. 4) we present some data that we believe to be challenging for both presented approaches; Sect. 5 draws conclusions.

Original languageEnglish
Title of host publicationLogic and Engineering of Natural Language Semantics - 20th International Conference, LENLS20, Revised Selected Papers
EditorsDaisuke Bekki, Koji Mineshima, Elin McCready
PublisherSpringer Science and Business Media Deutschland GmbH
Pages205-223
Number of pages19
ISBN (Print)9783031608773
DOIs
StatePublished - 2024
Event20th International Conference on Logic and Engineering of Natural Language Semantics, LENLS 2023 - Osaka, Japan
Duration: 18 Nov 202320 Nov 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14569 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Logic and Engineering of Natural Language Semantics, LENLS 2023
Country/TerritoryJapan
CityOsaka
Period18/11/2320/11/23

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

  • Argumentative analysis
  • Bayesian probability
  • Degree Semantics
  • Scalar Particles

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