Triple

T11618829
Position Surface form Disambiguated ID Type / Status
Subject Adana E275579 entity
Predicate hasSportsClub P346 FINISHED
Object Adana Demirspor E601026 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: Adana Demirspor | Statement: [Adana, hasSportsClub, Adana Demirspor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adana Demirspor
Context triple: [Adana, hasSportsClub, Adana Demirspor]
  • A. Adana Demirspor chosen
    Adana Demirspor is a Turkish professional football club based in Adana that competes in the country’s top leagues and has a passionate local fan base.
  • B. Adanaspor
    Adanaspor is a professional Turkish football club based in Adana that competes in the country’s league system and has featured various international players.
  • C. Denizlispor
    Denizlispor is a professional Turkish football club based in the city of Denizli that competes in the national league system.
  • D. Kayseri Erciyesspor
    Kayseri Erciyesspor is a Turkish professional football club based in Kayseri that has competed in the country’s top leagues under various names throughout its history.
  • E. Sakaryaspor
    Sakaryaspor is a Turkish professional football club known for developing notable talents such as legendary striker Hakan Şükür.
  • 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_69d6aaf84b548190ac072e4fb89ae18f completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a047758081908191c1d564409d9a completed April 10, 2026, 7:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee873ee6888190ab6e87ed0f4ae731 completed April 26, 2026, 9:44 p.m.
Created at: April 8, 2026, 9:38 p.m.