Triple
T10039048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zaza |
E205247
|
entity |
| Predicate | historicalRegion |
P915
|
FINISHED |
| Object | Bingöl |
E261264
|
NE 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: Bingöl | Statement: [Zaza, historicalRegion, Bingöl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bingöl Context triple: [Zaza, historicalRegion, Bingöl]
-
A.
Bingöl Province
chosen
Bingöl Province is an eastern Turkish province known for its mountainous landscape, Kurdish and Zaza populations, and rich local culture.
-
B.
Hakkâri
Hakkâri is a mountainous city in southeastern Turkey near the borders with Iraq and Iran, known for its rugged terrain and predominantly Kurdish population.
-
C.
Tunceli Province
Tunceli Province is a mountainous and sparsely populated region in eastern Turkey known for its significant Alevi and Zaza Kurdish population and its rugged natural landscapes.
-
D.
Muş Province
Muş Province is an eastern Turkish province known for its mountainous terrain, harsh continental climate, and predominantly Kurdish population.
-
E.
Elazığ Province
Elazığ Province is an eastern Turkish province known for its significant Zaza-speaking population, rich Anatolian history, and mountainous landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcee04afc8190904704d66e23a432 |
completed | April 2, 2026, 2:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff74d59f88190bbd975521b16ae49 |
completed | April 15, 2026, 8:38 p.m. |
Created at: March 30, 2026, 8:55 p.m.