Triple

T14581673
Position Surface form Disambiguated ID Type / Status
Subject Allie Quigley E342206 entity
Predicate hasPlayedFor P2170 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: [Allie Quigley, hasPlayedFor, Fenerbahçe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fenerbahçe
Context triple: [Allie Quigley, hasPlayedFor, 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. 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. Göztepe
    Göztepe is a coastal residential neighborhood in Istanbul, Turkey, known for its parks, seaside promenade, and location on the Asian side of the city.
  • 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_69d822ddc0f081909cd8163c7de298cd completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb41e71748190a1deacc819dd26d3 completed April 14, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5c57fa4819086912bdd2bda8b80 completed May 8, 2026, 12:23 p.m.
Created at: April 10, 2026, 1:24 a.m.