Triple
T12690813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altay S.K. |
E303197
|
entity |
| Predicate | rival |
P437
|
FINISHED |
| Object | Karşıyaka S.K. |
E63430
|
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: Karşıyaka S.K. | Statement: [Altay S.K., rival, Karşıyaka S.K.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karşıyaka S.K. Context triple: [Altay S.K., rival, Karşıyaka S.K.]
-
A.
Karşıyaka S.K.
chosen
Karşıyaka S.K. is a historic multi-sport club from the Karşıyaka district of İzmir, best known for its football team competing in the Turkish league system.
-
B.
Kocaelispor
Kocaelispor is a Turkish professional football club based in İzmit, known for its passionate fan base and regional rivalries in the Marmara region.
-
C.
Kayserispor
Kayserispor is a professional Turkish football club based in Kayseri that competes in the country’s top leagues.
-
D.
Denizlispor
Denizlispor is a professional Turkish football club based in the city of Denizli that competes in the national league system.
-
E.
Sakaryaspor
Sakaryaspor is a Turkish professional football club known for developing notable talents such as legendary striker Hakan Şükür.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961dabb38819087738361f9de8066 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c7a79908190b83a868090990bbe |
completed | May 2, 2026, 10:36 p.m. |
Created at: April 9, 2026, 5:22 p.m.