Triple

T10103057
Position Surface form Disambiguated ID Type / Status
Subject Didi E216248 entity
Predicate managedTeam P3234 FINISHED
Object Fenerbahçe SK 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 SK | Statement: [Didi, managedTeam, Fenerbahçe SK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fenerbahçe SK
Context triple: [Didi, managedTeam, Fenerbahçe SK]
  • 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. Fatih Karagümrük S.K.
    Fatih Karagümrük S.K. is a Turkish professional football club based in Istanbul that competes in the country’s top leagues and has attracted notable international managers and players.
  • D. Besiktas JK
    Beşiktaş JK is one of Turkey’s most prominent and historic multi-sport clubs, best known for its successful professional football team.
  • E. 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.
  • 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_69ca83d039f08190b9d10363221c69fb completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cdd09af07c819099774af46ebf62d7 completed April 2, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b6dcca848190851f6f1968fe244c completed April 5, 2026, 7:24 p.m.
Created at: March 30, 2026, 9:02 p.m.