Triple

T1435558
Position Surface form Disambiguated ID Type / Status
Subject Fenerbahçe SK E30551 entity
Predicate shortName P43 FINISHED
Object Fenerbahçe E30551 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: Fenerbahçe | Statement: [Fenerbahçe SK, shortName, Fenerbahçe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fenerbahçe
Context triple: [Fenerbahçe SK, shortName, Fenerbahçe]
  • A. Fenerbahce SK chosen
    Fenerbahçe SK is one of Turkey’s most prominent multi-sport clubs, best known for its successful football team and large, passionate fan base.
  • B. Galatasaray SK
    Galatasaray SK is a major Turkish multi-sport club best known for its successful football team, based in Istanbul.
  • C. Besiktas JK
    Beşiktaş JK is one of Turkey’s most prominent and historic multi-sport clubs, best known for its successful professional football team.
  • D. MKE Ankaragücü
    MKE Ankaragücü is a professional Turkish sports club best known for its football team, traditionally representing the capital city Ankara in the country’s top leagues.
  • E. Antalyaspor
    Antalyaspor is a professional Turkish football club based in Antalya that competes in the country’s top-tier league, the Süper Lig.
  • 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_69a498fc69ec8190b61722bd4b67c4d2 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c50250b88190a0fcf3e0cbba0b1a completed March 1, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad30877a348190a99dbeaf45cd0335 completed March 8, 2026, 8:17 a.m.
Created at: March 1, 2026, 8 p.m.