Knowledge of Maltese singular-plural mappings
Analogy explains it best
Bibliographic Data
| ID | 4580882 |
|---|---|
| Authors | Jessica Nieder (0000-0001-5977-8958, Heinrich Heine University Düsseldorf), Ruben Van De Vijver (0000-0003-0761-4649, Heinrich Heine University Düsseldorf), Holger Mitterer (0000-0003-4318-0032, University of Malta) |
| Year | 2021 |
| Volume | 31 |
| Issue | 2 |
| Pages | 147-170 |
| Publication date | 2021-05-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Morphology (JOURNAL) |
| Journal identifiers | ISSN: 1871-5621 • E-ISSN: 1871-5656 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11525-020-09353-7 |
| OpenAlex | W3012973865 |
| Language | EN |
| Citations received | 1 |
| References cited | 33 |
Which factors determine the choice of a plural allomorph for a new singular form? Are regular mappings stored differently from irregular mappings? Do native speakers only rely on analogical mappings to inflect novel word forms or do they use rules? To answer these questions we used data from Maltese, a language with a split morphology, which has a rich and variable set of concatenative and non-concatenative plural patterns.We conducted a production experiment, in which we investigated the mapping of a singular onto a plural. We show that this is driven by an interplay between the similarity of novel singular forms with existing singular words and their corresponding plural forms. Moreover, knowledge of the frequency of the plural patterns in the mental lexicon serves as a basis for generalization to novel words. Our results support an analogical model of morphological processing. We do not find evidence that native speakers use default rules
Allomorph · Basis (linear algebra · Generalization · Image (mathematics · Linguistics · Maltese · Mental lexicon · Morpheme · Natural language processing · Plural · Set (abstract data type · Similarity (geometry · Computer Science · Language and cultural evolution · Mathematics · Phonetics and Phonology Research · Syntax, Semantics, Linguistic Variation · Artificial Intelligence
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| Citations per year | 0.33 |
|---|---|
| Citation span | 2023 - 2023 (1) |
| Highly cited | No |