Triple

T12770534
Position Surface form Disambiguated ID Type / Status
Subject Karşıyaka S.K. E305236 entity
Predicate shortName P43 FINISHED
Object Karşıyaka SK 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 SK | Statement: [Karşıyaka S.K., shortName, Karşıyaka SK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karşıyaka SK
Context triple: [Karşıyaka S.K., shortName, Karşıyaka SK]
  • 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. Karşıyaka
    Karşıyaka is a populous coastal district of İzmir, Turkey, known for its vibrant urban life, historic neighborhoods, and strong local sports culture.
  • C. Kasımpaşa SK
    Kasımpaşa SK is a professional football club based in Istanbul, Turkey, that competes in the Turkish football league system.
  • D. Sakaryaspor
    Sakaryaspor is a Turkish professional football club known for developing notable talents such as legendary striker Hakan Şükür.
  • E. Sarıyer S.K.
    Sarıyer S.K. is a Turkish sports club best known for its football team representing the Sarıyer district of Istanbul.
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df4b36c81909bcc913dd5e535f8 completed April 10, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0dd657c8190b69e8bf187034360 completed May 3, 2026, 3:28 a.m.
Created at: April 9, 2026, 5:28 p.m.