Triple

T19155346
Position Surface form Disambiguated ID Type / Status
Subject Bromma E468914 entity
Predicate contains P35 FINISHED
Object Blackeberg 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: Blackeberg | Statement: [Bromma, contains, Blackeberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blackeberg
Context triple: [Bromma, contains, Blackeberg]
  • A. Blackeberg chosen
    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."
  • B. Enebyberg
    Enebyberg is a residential suburban area in the northern part of the Stockholm urban region in Sweden.
  • C. Rotebro
    Rotebro is a suburban district in the northern Stockholm area of Sweden, known for its residential neighborhoods and commuter connections.
  • D. Hägersten
    Hägersten is a residential district in southern Stockholm, Sweden, known for its mix of apartment blocks, green areas, and proximity to the city center.
  • 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_69d8dd084ff48190ac0f8c46ee722629 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5eeb914248190a92dc5f30cbc8fcc completed April 20, 2026, 9:15 a.m.
Created at: April 10, 2026, 12:06 p.m.