Triple

T3272106
Position Surface form Disambiguated ID Type / Status
Subject Hamar E68670 entity
Predicate hasSportsClub P346 FINISHED
Object Hamarkameratene E331579 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: Hamarkameratene | Statement: [Hamar, hasSportsClub, Hamarkameratene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamarkameratene
Context triple: [Hamar, hasSportsClub, Hamarkameratene]
  • A. Hamarkameratene chosen
    Hamarkameratene is a Norwegian football club based in the town of Hamar, known for competing in the national league system.
  • B. Skedsmo
    Skedsmo is a former municipality in Viken county, Norway, located northeast of Oslo and known for its suburban communities and historical ties to the Oslo region.
  • C. Frolands Verk
    Frolands Verk is a small village in Froland municipality in Agder county, Norway, historically known for its ironworks and industrial heritage.
  • D. Øyer
    Øyer is a small municipality in Innlandet county, Norway, known for its rural valley landscape and proximity to the Hafjell ski resort.
  • E. Rødenes
    Rødenes is a small village and former municipality in southeastern Norway, known for its rural landscape and historic church.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adaff6308881908886a44804a0bb09 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28f0793e08190af55ee16e5091451 completed March 12, 2026, 10:01 a.m.
Created at: March 8, 2026, 3:10 p.m.