Triple

T21288621
Position Surface form Disambiguated ID Type / Status
Subject Norwegian Government Quarter E524727 entity
Predicate cityBlockBoundedBy P43688 FINISHED
Object Grubbegata NE NERFINISHED

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: Grubbegata | Statement: [Norwegian Government Quarter, cityBlockBoundedBy, Grubbegata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grubbegata
Context triple: [Norwegian Government Quarter, cityBlockBoundedBy, Grubbegata]
  • A. Grubbegata chosen
    Grubbegata is a street in central Oslo, Norway, known for running through the area that houses key government buildings and institutions.
  • B. Rosengård
    Rosengård is a prominent Swedish football club based in Malmö, known for its successful women's team and history of developing world-class players.
  • C. Blackeberg
    Blackeberg is a suburban district in western Stockholm, Sweden, best known internationally as the bleak, wintry backdrop of the Swedish vampire novel and film "Let the Right One In."
  • D. Lilla Nygatan
    Lilla Nygatan is a historic street in Stockholm’s Old Town (Gamla stan), known for its preserved medieval character and traditional urban streetscape.
  • E. Kungsbacka
    Kungsbacka is a town in southwestern Sweden known for its coastal location, historic wooden center, and role as a commuter hub for nearby Gothenburg.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736d882408190a2300327cb73b7f6 completed April 21, 2026, 8:35 a.m.
Created at: April 16, 2026, 4:03 p.m.