Hybrid agreement in English
Datos Bibliográficos
| ID | 4958366 |
|---|---|
| Autores | J B Kim (0000-0003-3286-0446, Kyung Hee University, autor de correspondencia), Jong-Bok Kim |
| Año | 2004 |
| Volumen | 42 |
| Número | 6 |
| Fecha de publicación | 2004-01-13 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Linguistics (JOURNAL) |
| Identificadores de la revista | ISSN: 0024-3949 • E-ISSN: 1613-396X |
| Editorial | Walter de Gruyter GmbH (PUBLISHER • DE) |
| DOI | 10.1515/ling.2004.42.6.1105 |
| OpenAlex | W1994955953 |
| Idioma | EN |
| Citas recibidas | 5 |
| Referencias citadas | 7 |
Most of the previous approaches to English agreement phenomena have relied upon only one component of the grammar (e.g., either syntax, or semantics, or pragmatics). This paper argues that interrelationships among different grammatical components play crucial roles in such phenomenon too (cf. Kathol 1999 and Hudson 1999). The paper proposes that contrary to traditional wisdom English determiner-noun agreement is morpho-syntactic whereas subject-verb and pronoun-antecedent agreement are reflections of index agreement (cf. Pollard and Sag 1994). The present hybrid analysis of English agreement shows that the importance of the interaction of different components of the grammar in accounting for English agreement phenomena. In particular, once we allow morphology to tightly interact with the system of syntax, semantics, or even pragmatics, we could provide a solution to some puzzling English agreement phenomena. This allows a more principled theory of English agreement. 1
Agreement · Antecedent (behavioral psychology) · Determiner · English grammar · Grammar · Linguistics · Noun · Pragmatics · Semantics (computer science) · Subject (documents) · Syntax · Verb · Artificial Intelligence · Computer Science · Language, Discourse, Communication Strategies · Linguistic Variation and Morphology · Philosophy · Psychology · Syntax, Semantics, Linguistic Variation
| Obras citantes distintas | 5 |
|---|---|
| Citas por año | 0,26 |
| Intervalo de citas | 2007 - 2024 (18) |
| Velocidad de citación | recent |
| Altamente citado | No |
| Tipos de cita | Neutras: 5 |