Triple
T2986866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gençlerbirliği S.K. |
E80645
|
entity |
| Predicate | president |
P8
|
FINISHED |
| Object | Niyazi Akdaş |
E324366
|
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: Niyazi Akdaş | Statement: [Gençlerbirliği S.K., president, Niyazi Akdaş]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niyazi Akdaş Context triple: [Gençlerbirliği S.K., president, Niyazi Akdaş]
-
A.
Niyazi Akdaş
chosen
Niyazi Akdaş is a Turkish football executive best known for serving as chairman of the Ankara-based club Gençlerbirliği S.K.
-
B.
Tahsin Özgüç
Tahsin Özgüç was a prominent Turkish archaeologist renowned for his pioneering research on ancient Anatolian civilizations.
-
C.
Hidayet Karaca
Hidayet Karaca is a Turkish media executive best known as the former head of the Samanyolu Broadcasting Group and a prominent figure associated with the Gülen movement.
-
D.
Melih Gökçek
Melih Gökçek is a Turkish politician best known for his long tenure as the mayor of Ankara and his prominent role in conservative Islamist politics.
-
E.
Metin Feyzioğlu
Metin Feyzioğlu is a prominent Turkish lawyer, academic, and former president of the Union of Turkish Bar Associations.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c88f608190bf734e0b744bf3d1 |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2033e50988190a99bca343923b099 |
completed | March 12, 2026, 12:05 a.m. |
Created at: March 8, 2026, 2:59 p.m.