Triple
T13917981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modern Uyghur |
E334670
|
entity |
| Predicate | usesCaseMarkers |
P23828
|
FINISHED |
| Object | postpositions |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: postpositions | Statement: [Modern Uyghur, usesCaseMarkers, postpositions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCaseMarkers Context triple: [Modern Uyghur, usesCaseMarkers, postpositions]
-
A.
hasCaseMarking
Indicates that a linguistic element (such as a noun or pronoun) bears a specific grammatical case marking that signals its syntactic or semantic role in a clause.
-
B.
usesCaseHarmony
Indicates that one element selects or governs another element such that their grammatical cases are compatible or harmonized according to the language’s case system.
-
C.
usesCaseSystem
chosen
Indicates that one entity employs or operates using a particular case system (e.g., grammatical or structural case-marking system).
-
D.
usedInCase
Indicates that something (such as an item, method, or piece of information) is employed or applied within a particular case or instance.
-
E.
usedMark
Indicates that one entity has employed or applied a particular mark, symbol, or indicator in some context or action.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de272753e48190bc609482635280ff |
completed | April 14, 2026, 11:38 a.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.