The morphosyntax of Ezafe in Southern Zazaki
Bibliographic record
Abstract
Abstract The present study describes and analyzes the morphosyntactic expression of the Southern Zazaki Ezafe – a linking element in the nominal domain common among Iranian languages. This morpheme is used to link modifiers (i.e. adjectives and possessors) to their head nouns as follows: n-ez1 mod1-ez2 mod2-ez3 mod3. Southern Zazaki, like other languages of the Kurdish region (and unlike, e.g. Persian) reflects phi-features (and case) of the head noun on each Ezafe morpheme in a noun phrase. This paper is focussed around two morphosyntactic puzzles that arise in Southern Zazaki. First, while the Ezafe marker in general reflects the case of the entire DP, the presence of a possessor produces invariant oblique case, regardless of the case value assigned to the DP externally (Paul, Ludwig. 2009. Zazaki. In Gernot Windfuhr (ed.), The Iranian languages, 545–586. Routledge; Todd, Terry Lynn. 2002. A grammar of Dimili. Also known as Zaza. Stockholm: Iremet Forlag; Toosarvandani, Maziar & Coppe van Urk. 2014. The syntax of nominal concord: What Ezafe in Zazaki shows us. Proceedings of NELS 43(2). 209–220 i.a.). Second, Southern Zazaki uniquely employs a separate series of “D-form” Ezafe morphemes in certain syntactic contexts (Keskin, Mesut. 2010. Zazaca üzerine notlar (Notes on Zazaki). In Şükrü Aslan (ed.), Herkesin Bildiugi Sır: Dersim. Iletisim, 221–244; Paul, Ludwig. 2009. Zazaki. In Gernot Windfuhr (ed.), The Iranian languages, 545–586. Routledge; Todd, Terry Lynn. 2002. A grammar of Dimili. Also known as Zaza. Stockholm: Iremet Forlag; Werner, Brigitte. 2018. Forms and meanings of the Ezafe in Zazaki. In Saloumeh Gholami (ed.), Endangered Iranian languages. Reichert Verlag i.a.). This study aims to provide a cohesive analysis of Ezafe in Southern Zazaki both with respect to its general phi- and case-sensitive realizations, as well as the distribution of D-forms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".