Triple

T5805193
Position Surface form Disambiguated ID Type / Status
Subject Haderslev E128727 entity
Predicate hasSportsClub P346 FINISHED
Object Haderslev FK
Haderslev FK is a Danish football club based in the town of Haderslev.
E546978 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: Haderslev FK | Statement: [Haderslev, hasSportsClub, Haderslev FK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haderslev FK
Context triple: [Haderslev, hasSportsClub, Haderslev FK]
  • A. TuS Herten
    TuS Herten is a German basketball club where future NBA coach Erik Spoelstra played professionally early in his career.
  • B. Vendsyssel FF
    Vendsyssel FF is a Danish professional football club based in the town of Hjørring in northern Jutland.
  • C. FC Midtjylland
    FC Midtjylland is a Danish professional football club known for its data-driven approach to player recruitment and performance, competing in the top tier of Danish football.
  • D. 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.
  • E. Aarhus Håndbold
    Aarhus Håndbold is a professional handball club based in Aarhus, Denmark, competing in the Danish handball league system.
  • 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: Haderslev FK
Triple: [Haderslev, hasSportsClub, Haderslev FK]
Generated description
Haderslev FK is a Danish football club based in the town of Haderslev.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Haderslev FK
Target entity description: Haderslev FK is a Danish football club based in the town of Haderslev.
  • A. TuS Herten
    TuS Herten is a German basketball club where future NBA coach Erik Spoelstra played professionally early in his career.
  • B. Vendsyssel FF
    Vendsyssel FF is a Danish professional football club based in the town of Hjørring in northern Jutland.
  • C. FC Midtjylland
    FC Midtjylland is a Danish professional football club known for its data-driven approach to player recruitment and performance, competing in the top tier of Danish football.
  • D. 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.
  • E. Aarhus Håndbold
    Aarhus Håndbold is a professional handball club based in Aarhus, Denmark, competing in the Danish handball league system.
  • 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_69c00846a0d881909e46841f8e156b64 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02b1461a48190be2042dd3823d02e completed March 22, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09836d00881908c210b2932d67519 completed March 23, 2026, 1:32 a.m.
NEDg Description generation batch_69c098f32f7081908d9306afc30147a1 completed March 23, 2026, 1:35 a.m.
NED2 Entity disambiguation (via description) batch_69c0996fb9148190ae8c09f4816d00b8 completed March 23, 2026, 1:37 a.m.
Created at: March 22, 2026, 3:52 p.m.