Triple
T22657532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Şenol Güneş |
E559267
|
entity |
| Predicate | managedTeam |
P3234
|
FINISHED |
| Object | Boluspor |
—
|
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: Boluspor | Statement: [Şenol Güneş, managedTeam, Boluspor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boluspor Context triple: [Şenol Güneş, managedTeam, Boluspor]
-
A.
Boluspor
chosen
Boluspor is a Turkish professional football club based in the city of Bolu that competes in the country’s football league system.
-
B.
Bursaspor
Bursaspor is a professional Turkish sports club best known for its football team, which has competed in the country’s top leagues and is based in the city of Bursa.
-
C.
Sakaryaspor
Sakaryaspor is a Turkish professional football club known for developing notable talents such as legendary striker Hakan Şükür.
-
D.
Tuzlaspor
Tuzlaspor is a Turkish professional football club based in the Tuzla district of Istanbul that competes in the country's league system.
-
E.
Konyaspor
Konyaspor is a professional Turkish football club based in Konya that competes in the country’s top leagues and has a passionate regional fan base.
- 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_69e245489dd88190b1f674acf61c8769 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1765c62bc8190b3fcde76d6b6dfb6 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 3:06 p.m.