Triple
T25095342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niamey Zarma |
E628572
|
entity |
| Predicate | principalUrbanDialectOf |
P35609
|
FINISHED |
| Object | Zarma language |
—
|
NE NERFINISHED |
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: Zarma language | Statement: [Niamey Zarma, principalUrbanDialectOf, Zarma language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: principalUrbanDialectOf Context triple: [Niamey Zarma, principalUrbanDialectOf, Zarma language]
-
A.
regionalDialect
Indicates that one entity uses or is associated with a dialect specific to a particular geographic region in relation to another entity.
-
B.
majorDialectOf
Indicates that one dialect is the primary or most prominent dialect associated with a particular language or region.
-
C.
spokenInUrbanArea
Indicates that an utterance or speech event occurs within a city or densely populated urban environment.
-
D.
dominantDialect
Indicates that one dialect is the primary or most influential form of a language within a particular context or region.
-
E.
majorCityWhereSpoken
chosen
Indicates that a language or dialect is commonly spoken in the specified major city.
- 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_69e2ff2f58e881908340527bc5d34f07 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f46d3f35848190b56a4373c97a7d64 |
completed | May 1, 2026, 9:07 a.m. |
| PD | Predicate disambiguation | batch_69f4683472ec8190a483b3b8afe71720 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 6:24 a.m.