Triple

T6149073
Position Surface form Disambiguated ID Type / Status
Subject Stabæk Fotball E137150 entity
Predicate homeCity P263 FINISHED
Object Bekkestua E164673 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: Bekkestua | Statement: [Stabæk Fotball, homeCity, Bekkestua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bekkestua
Context triple: [Stabæk Fotball, homeCity, Bekkestua]
  • A. Bekkestua chosen
    Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
  • B. Bålsta
    Bålsta is a locality in Uppsala County, Sweden, known as the main urban center of Håbo Municipality and a commuter town within the Greater Stockholm region.
  • C. Sørenga
    Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
  • D. Finnsnes
    Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
  • E. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • 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_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_69c7941f24b881908aeb02b2cae78e12 completed March 28, 2026, 8:41 a.m.
Created at: March 22, 2026, 4:16 p.m.