Triple

T6149052
Position Surface form Disambiguated ID Type / Status
Subject Stabæk Fotball E137150 entity
Predicate partOf P40 FINISHED
Object Stabæk IF
Stabæk IF is a Norwegian multi-sport club best known for its professional football team, Stabæk Fotball, based in Bærum.
 E137150 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: Stabæk IF | Statement: [Stabæk Fotball, partOf, Stabæk IF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stabæk IF
Context triple: [Stabæk Fotball, partOf, Stabæk IF]
  • A. Stabæk Fotball
    Stabæk Fotball is a Norwegian professional football club based in Bærum, known for competing in the country’s top divisions and developing notable players and coaches.
  • B. Viking FK
    Viking FK is a Norwegian professional football club based in Stavanger that competes in the country’s top division, the Eliteserien.
  • C. Rosenborg BK
    Rosenborg BK is a Norwegian professional football club from Trondheim, historically one of the country’s most successful teams and a dominant force in the Eliteserien.
  • D. Bryne FK
    Bryne FK is a Norwegian football club known for developing striker Erling Haaland in its youth system.
  • E. Vålerenga
    Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
  • 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: Stabæk IF
Triple: [Stabæk Fotball, partOf, Stabæk IF]
Generated description
Stabæk IF is a Norwegian multi-sport club best known for its professional football team, Stabæk Fotball, based in Bærum.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stabæk IF
Target entity description: Stabæk IF is a Norwegian multi-sport club best known for its professional football team, Stabæk Fotball, based in Bærum.
  • A. Stabæk Fotball chosen
    Stabæk Fotball is a Norwegian professional football club based in Bærum, known for competing in the country’s top divisions and developing notable players and coaches.
  • B. Viking FK
    Viking FK is a Norwegian professional football club based in Stavanger that competes in the country’s top division, the Eliteserien.
  • C. Rosenborg BK
    Rosenborg BK is a Norwegian professional football club from Trondheim, historically one of the country’s most successful teams and a dominant force in the Eliteserien.
  • D. Bryne FK
    Bryne FK is a Norwegian football club known for developing striker Erling Haaland in its youth system.
  • E. Vålerenga
    Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
  • F. None of above.

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_69c008a2c6308190a56519b22d55d083 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05ce21820819096be9159d6b70a5f completed March 22, 2026, 9:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c518e697088190b47a610783baa7ea completed March 26, 2026, 11:30 a.m.
NEDg Description generation batch_69c51e1f031c819099eeec59da88bae9 completed March 26, 2026, 11:53 a.m.
NED2 Entity disambiguation (via description) batch_69c51eacb37c819080f139b8f4f2f38c completed March 26, 2026, 11:55 a.m.
Created at: March 22, 2026, 4:16 p.m.