Triple

T22281622
Position Surface form Disambiguated ID Type / Status
Subject Glostrup E550744 entity
Predicate hasSportsClub P346 FINISHED
Object Glostrup FK
Glostrup FK is a Danish football club based in the town of Glostrup.
E1528592 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: Glostrup FK | Statement: [Glostrup, hasSportsClub, Glostrup FK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Glostrup FK
Context triple: [Glostrup, hasSportsClub, Glostrup FK]
  • A. Haderslev FK
    Haderslev FK is a Danish football club based in the town of Haderslev.
  • B. Viborg FF
    Viborg FF is a Danish professional football club based in Viborg that competes in the Danish Superliga.
  • C. Hvidovre IF
    Hvidovre IF is a Danish football club known for developing notable players, including legendary goalkeeper Peter Schmeichel.
  • D. Holstebro Boldklub
    Holstebro Boldklub is a Danish football club based in the town of Holstebro, competing in the lower tiers of the national league system and focusing on both senior and youth development.
  • E. Næstved Boldklub
    Næstved Boldklub is a Danish football club based in the town of Næstved, known for competing in the national league system and developing local talent.
  • 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: Glostrup FK
Triple: [Glostrup, hasSportsClub, Glostrup FK]
Generated description
Glostrup FK is a Danish football club based in the town of Glostrup.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Glostrup FK
Target entity description: Glostrup FK is a Danish football club based in the town of Glostrup.
  • A. Haderslev FK
    Haderslev FK is a Danish football club based in the town of Haderslev.
  • B. Viborg FF
    Viborg FF is a Danish professional football club based in Viborg that competes in the Danish Superliga.
  • C. Hvidovre IF
    Hvidovre IF is a Danish football club known for developing notable players, including legendary goalkeeper Peter Schmeichel.
  • D. Holstebro Boldklub
    Holstebro Boldklub is a Danish football club based in the town of Holstebro, competing in the lower tiers of the national league system and focusing on both senior and youth development.
  • E. Næstved Boldklub
    Næstved Boldklub is a Danish football club based in the town of Næstved, known for competing in the national league system and developing local talent.
  • 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_69e11e44d538819097c6b8f333af3352 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f14eac0994819088e39a1b5d39cf18 completed April 29, 2026, 12:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0abcaa46788190970d08e2328d5503 completed May 18, 2026, 7:15 a.m.
NEDg Description generation batch_6a0abdba268881908b936c0abf539a39 completed May 18, 2026, 7:20 a.m.
NED2 Entity disambiguation (via description) batch_6a0abf213878819085413d22a824fe58 completed May 18, 2026, 7:26 a.m.
Created at: April 16, 2026, 8:40 p.m.