On apparent pronominal feature contradictions
Shifty agreement in Telugu
Dados Bibliográficos
| ID | 4238152 |
|---|---|
| Autores | Troy Messick (0000-0002-1453-5212, Rutgers, the State University of New Jersey, autor correspondente) |
| Ano | 2023 |
| Volume | 26 |
| Fascículo | 2 |
| Páginas | 137-182 |
| Data de publicação | 2023-06-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Syntax (JOURNAL) |
| Identificadores do periódico | ISSN: 1368-0005 • E-ISSN: 1467-9612 |
| Editora | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/synt.12248 |
| OpenAlex | W4321596395 |
| Idioma | EN |
| Citações recebidas | 2 |
| Referências citadas | 47 |
This article investigates so-called monstrous agreement-where a non-first-person pronoun can control first-person agreement on an embedded verb-in Telugu. Empirically, I provide the most in-depth description of monstrous agreement in Telugu to date. To account for monstrous agreement, I propose that embedded pronouns have morphosyntactic features that indicate their roles in both the matrix and embedded speech acts. This means an embedded pronoun can have first-person and third- or second-person features simultaneously. I then propose a precise set of morphosyntactic operations that allow the first-person feature to appear on the verbal agreement but not the pronoun controlling the agreement. I also show that pronouns that have these contradictory features must be bound by an operator to be licensed, and I discuss the nature of these operators and the locality conditions on the binding relationship. The theoretical consequence of this article is that apparently contradictory feature combinations on pronominal elements must be sanctioned by UG
Agreement · Feature (linguistics · Linguistics · Locality · Natural language processing · Object pronoun · Pronoun · Set (abstract data type · Telugu · Verb · Computer Science · Language, Discourse, Communication Strategies · Natural Language Processing Techniques · Philosophy · Syntax, Semantics, Linguistic Variation · Artificial Intelligence
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| Obras citantes distintas | 2 |
|---|---|
| Citações por ano | 0,67 |
| Intervalo de citações | 2023 - 2024 (2) |
| Velocidade de citação | recent |
| Altamente citado | Não |
| Tipos de citação | Neutras: 2 |