Triple

T6776243
Position Surface form Disambiguated ID Type / Status
Subject Herning Blue Fox E155161 entity
Predicate formerName P65 FINISHED
Object Herning IK
Herning IK is the former name of Herning Blue Fox, a professional ice hockey club based in Herning, Denmark.
E618272 NE FINISHED

How this triple was built (4 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: Herning IK | Statement: [Herning Blue Fox, formerName, Herning IK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herning IK
Context triple: [Herning Blue Fox, formerName, Herning IK]
  • A. Haderslev FK
    Haderslev FK is a Danish football club based in the town of Haderslev.
  • B. TuS Herten
    TuS Herten is a German basketball club where future NBA coach Erik Spoelstra played professionally early in his career.
  • C. Aarhus Håndbold
    Aarhus Håndbold is a professional handball club based in Aarhus, Denmark, competing in the Danish handball league system.
  • D. Vendsyssel FF
    Vendsyssel FF is a Danish professional football club based in the town of Hjørring in northern Jutland.
  • E. Akademisk Boldklub
    Akademisk Boldklub is a historic Danish football club based in Copenhagen, known for its strong ties to academia and its role in early Danish football history.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Herning IK
Triple: [Herning Blue Fox, formerName, Herning IK]
Generated description
Herning IK is the former name of Herning Blue Fox, a professional ice hockey club based in Herning, Denmark.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Herning IK
Target entity description: Herning IK is the former name of Herning Blue Fox, a professional ice hockey club based in Herning, Denmark.
  • A. Haderslev FK
    Haderslev FK is a Danish football club based in the town of Haderslev.
  • B. TuS Herten
    TuS Herten is a German basketball club where future NBA coach Erik Spoelstra played professionally early in his career.
  • C. Aarhus Håndbold
    Aarhus Håndbold is a professional handball club based in Aarhus, Denmark, competing in the Danish handball league system.
  • D. Vendsyssel FF
    Vendsyssel FF is a Danish professional football club based in the town of Hjørring in northern Jutland.
  • E. Akademisk Boldklub
    Akademisk Boldklub is a historic Danish football club based in Copenhagen, known for its strong ties to academia and its role in early Danish football history.
  • F. None of above. chosen

Provenance (5 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_69c68812ef7c819099369f51febb725c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d24f77c88190be21cf4ef132aa31 completed March 27, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712cc9ff08190bb7ec0bf4cc4db01 completed March 27, 2026, 11:29 p.m.
NEDg Description generation batch_69c71396f1f88190b3316e694424a2fe completed March 27, 2026, 11:32 p.m.
NED2 Entity disambiguation (via description) batch_69c71466728c81909a24174a7938b43a completed March 27, 2026, 11:36 p.m.
Created at: March 27, 2026, 2:13 p.m.