Triple

T11753840
Position Surface form Disambiguated ID Type / Status
Subject Joachim Löw E279473 entity
Predicate managedTeam P3234 FINISHED
Object Adanaspor E893639 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: Adanaspor | Statement: [Joachim Löw, managedTeam, Adanaspor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adanaspor
Context triple: [Joachim Löw, managedTeam, Adanaspor]
  • A. Adanaspor chosen
    Adanaspor is a professional Turkish football club based in Adana that competes in the country’s league system and has featured various international players.
  • B. Adana Demirspor
    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.
  • C. Sakaryaspor
    Sakaryaspor is a Turkish professional football club known for developing notable talents such as legendary striker Hakan Şükür.
  • D. Alanyaspor
    Alanyaspor is a professional Turkish football club based in Alanya that competes in the country’s top leagues and is known for its regional rivalry with Antalyaspor.
  • E. Kayserispor
    Kayserispor is a professional Turkish football club based in Kayseri that competes 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a50b8a14819092a7397d73f0a8e3 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f01a21559c819097d0287dd8e2f411 completed April 28, 2026, 2:23 a.m.
Created at: April 8, 2026, 9:41 p.m.