Anti-Ikonizität an der Syntax-Semantik-Schnittstelle
Bibliographic Data
| ID | 19415482 |
|---|---|
| Authors | Markus Egg (0000-0002-7351-9175, Centre for Language and Cognition Rijksuniversiteit Groningen, Germany, corresponding author) |
| Year | 2006 |
| Volume | 25 |
| Issue | 1 |
| Pages | 1-38 |
| Publication date | 2006-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Zeitschrift für Sprachwissenschaft (JOURNAL) |
| Journal identifiers | ISSN: 0721-9067 • E-ISSN: 1613-3706 |
| Publisher | Walter de Gruyter GmbH (PUBLISHER • DE) |
| DOI | 10.1515/zfs.2006.001 |
| OpenAlex | W2519060412 |
| Language | EN |
| Citations received | 5 |
| References cited | 13 |
The syntax-semantics interface is iconic in that it maps syntactic asymmetries (in particular, unilateral c-command) onto semantic asymmetries (scope relations). But many modification structures seem to violate this iconicity: here the modifier has (optionally or obligatorily) semantic scope over only a part of the expression that it modifies syntactically. First I will show that some well-known cases of syntax-semantics mismatch are instances of this phenomenon. Then I will specify an extremely flexible syntax-semantics interface to handle the apparent anti-iconicity. This interface crucially relies on the expressive power of a suitable underspecification formalism. With the interface one can derive the semantic representations of the problematic examples from surface-oriented syntactic structures without giving up the iconicity between syntax and semantics.Apparent anti-iconicity eventually emerges as scope underspecification between a modifier and part of the expression that it modifies. The analysis is applied to German and Turkish data
Abstract syntax · Iconicity · Linguistics · Natural language processing · Principle of compositionality · Programming language · Syntax · Underspecification · Computer Science · Historical Linguistics and Language Studies · Linguistic research and analysis · Philosophy · Syntax, Semantics, Linguistic Variation · Artificial Intelligence
| Citations per year | 0.24 |
|---|---|
| Citation span | 2005 - 2020 (16) |
| Highly cited | No |