Triple
T11287226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sivas Province |
E267227
|
entity |
| Predicate | ethnicGroup |
P194
|
FINISHED |
| Object | Zazas |
E901391
|
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: Zazas | Statement: [Sivas Province, ethnicGroup, Zazas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zazas Context triple: [Sivas Province, ethnicGroup, Zazas]
-
A.
Zazas
chosen
The Zazas are an Iranian ethnic group primarily inhabiting eastern Turkey, known for speaking the Zaza (Dimili) language and maintaining distinct cultural traditions.
-
B.
Zabdas
Zabdas was a prominent 3rd-century Palmyrene general who led Queen Zenobia’s forces in major campaigns against the Roman Empire.
-
C.
Zas
Zas is a municipality in the province of A Coruña in Galicia, northwestern Spain, known for its rural landscapes and traditional Galician culture.
-
D.
Zog
Zog is a children's picture book by Julia Donaldson, illustrated by Axel Scheffler, about an eager young dragon learning at dragon school.
-
E.
Zardoz
Zardoz is a 1974 science fiction film directed by John Boorman, known for its surreal, dystopian vision and starring Sean Connery in one of his most unconventional roles.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e986b0f08190a414749eaa7f1a5d |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f48e190c8190b46d4286e2acaef1 |
completed | April 19, 2026, 3:28 p.m. |
Created at: April 8, 2026, 9:32 p.m.