Triple
T22262098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limak |
E550251
|
entity |
| Predicate | hasKeyPerson |
P256
|
FINISHED |
| Object | Nihat Özdemir |
—
|
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: Nihat Özdemir | Statement: [Limak, hasKeyPerson, Nihat Özdemir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nihat Özdemir Context triple: [Limak, hasKeyPerson, Nihat Özdemir]
-
A.
Nihat Özdemir
chosen
Nihat Özdemir is a prominent Turkish businessman and sports executive, best known as the founder of Limak Holding and a former president of the Turkish Football Federation.
-
B.
Tahsin Banguoğlu
Tahsin Banguoğlu was a Turkish linguist, academic, and politician known for his influential work on Turkish language and grammar.
-
C.
Levent Öktem
Levent Öktem is a Turkish actor known for his roles in television dramas and films, including the historical series "Diriliş: Ertuğrul."
-
D.
Murat Aysan
Murat Aysan is a Turkish businessman best known to the public as the husband of actress Nur Fettahoğlu.
-
E.
Mehmet Ali Şahin
Mehmet Ali Şahin is a Turkish politician who has served in prominent roles including Speaker of the Grand National Assembly and Minister of Justice.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141b87de0819088b7553406343068 |
completed | April 28, 2026, 11:24 p.m. |
Created at: April 16, 2026, 8:39 p.m.