Triple

T5431022
Position Surface form Disambiguated ID Type / Status
Subject Segeltorp E121488 entity
Predicate hasNeighbouringArea P17964 FINISHED
Object Skärholmen E378324 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: Skärholmen | Statement: [Segeltorp, hasNeighbouringArea, Skärholmen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skärholmen
Context triple: [Segeltorp, hasNeighbouringArea, Skärholmen]
  • A. Skärholmen chosen
    Skärholmen is a suburban district in southwestern Stockholm, Sweden, known for its large shopping center and residential areas.
  • B. Kastellholmen
    Kastellholmen is a small island in central Stockholm, Sweden, known for its historic red-brick citadel and scenic waterfront views.
  • C. Skarpö
    Skarpö is an island in the Stockholm archipelago of Sweden, situated within Vaxholm Municipality and known for its coastal scenery and residential character.
  • D. Storholmen
    Storholmen is an island located in Lake Femunden, one of Norway’s largest inland lakes.
  • E. Kvarnholmen
    Kvarnholmen is a former industrial island district in the Stockholm area that has been transformed into a modern residential and waterfront neighborhood.
  • 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_69bd463c65f0819082ee6483ab4b466a completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd883e5e10819091e159dfd245e94d completed March 20, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3ac6285081909afa6e91a023f6d5 completed March 22, 2026, 12:41 a.m.
Created at: March 20, 2026, 2:06 p.m.