Triple

T1453939
Position Surface form Disambiguated ID Type / Status
Subject Beşiktaş JK E31354 entity
Predicate location P40 FINISHED
Object Beşiktaş E31354 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: Beşiktaş | Statement: [Beşiktaş JK, location, Beşiktaş]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beşiktaş
Context triple: [Beşiktaş JK, location, Beşiktaş]
  • A. Galatasaray SK
    Galatasaray SK is a major Turkish multi-sport club best known for its successful football team, based in Istanbul.
  • B. Fenerbahce SK
    Fenerbahçe SK is one of Turkey’s most prominent multi-sport clubs, best known for its successful football team and large, passionate fan base.
  • C. Besiktas JK chosen
    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. Göztepe S.K.
    Göztepe S.K. is a professional Turkish football club based in İzmir, known for its passionate fan base and historic presence in Turkish football.
  • 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_69a499171a28819085b993a3ac78e363 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c57e82d48190a30a4512f39f5de0 completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad36fd91488190b0431bc1c83c64e3 completed March 8, 2026, 8:44 a.m.
Created at: March 1, 2026, 8 p.m.