Triple
T16365290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kistane language |
E397420
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Kistane |
E1208514
|
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: Kistane | Statement: [Kistane language, alternativeName, Kistane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kistane Context triple: [Kistane language, alternativeName, Kistane]
-
A.
Kistane
chosen
Kistane is an Afroasiatic language of the Highland East Cushitic branch spoken primarily by the Soddo Gurage people in central Ethiopia.
-
B.
Cerezo
Cerezo is a Spanish surname most notably associated with Enrique Cerezo, a prominent film producer and president of Atlético Madrid.
-
C.
Kastania
Kastania is a small settlement in Greece located close to Mount Ziria in the Peloponnese region.
-
D.
Kastania
Kastania is a small settlement in Greece located near the area of Kyllini in the western Peloponnese.
-
E.
Kiraz
Kiraz is a rural district and town in western Turkey known for its agricultural production, particularly cherries, within İzmir Province.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2ff3c915c81909e1757fc31921876 |
completed | April 18, 2026, 3:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0035600420819087c909a615d205a2 |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:08 a.m.