Tense as a Grammatical Category in Sinitic

A Critical Overview

Datos Bibliográficos

ID5899892
AutoresGiorgio Francesco Arcodia (0000-0002-7324-8352, Ca' Foscari University of Venice, autor de correspondencia)
Año2023
Volumen8
Número2
Páginas142
Fecha de publicación2023-05-30
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaLanguages (JOURNAL)
Identificadores de la revistaISSN: 2226-471X • E-ISSN: 2226-471X
EditorialMDPI AG (PUBLISHER • IT)
DOI10.3390/languages8020142
OpenAlexW4378907245
IdiomaEN
Citas recibidas2
Referencias citadas24

Sinitic languages are very often described as tenseless, since they are generally seen as lacking 'true' grammatical markers of tense: thus, the interpretation of time reference relies on other factors, such as aspect, modal verbs, and the use of time expressions. However, the debate concerning the tenseless nature of Chinese has not been settled yet: several types of items in Sinitic have been analyzed as expressing both aspect and tense, tense and modality, or even tense only. In this paper, we offer a critical analysis of the proposals made in the description of Standard Mandarin Chinese and (so-called) Chinese dialects concerning grammatical exponents of tense. We shall show that there appears to be a very broad degree of variation within Sinitic in the type and nature of tense(-like) meanings expressed, with different degrees of overlap between tense and other TAM categories (i.e., aspect and modality), and different degrees of grammaticalisation of alleged tense markers. Furthermore, the most grammaticalised tense markers are located in subregions within northern China: we shall thus discuss the relevance of our data for the areal typology of Sinitic

Future tense · Grammatical category · Grammaticalization · Linguistics · Mandarin Chinese · Modality (human–computer interaction · Physics · Present tense · Typology · Variation (astronomy · Verb · Computer Science · History · Linguistic Variation and Morphology · Philosophy · Phonetics and Phonology Research · Syntax, Semantics, Linguistic Variation · Artificial Intelligence