Triple

T5431023
Position Surface form Disambiguated ID Type / Status
Subject Segeltorp E121488 entity
Predicate hasNeighbouringArea P17964 FINISHED
Object Vårby E126479 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: Vårby | Statement: [Segeltorp, hasNeighbouringArea, Vårby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vårby
Context triple: [Segeltorp, hasNeighbouringArea, Vårby]
  • A. Vårby chosen
    Vårby is a suburban district in the southern Stockholm area of Sweden, known for its residential neighborhoods and proximity to Lake Mälaren.
  • B. Viggbyholm
    Viggbyholm is a residential urban area in the northern Stockholm region of Sweden, known for its proximity to water, green spaces, and commuter connections into central Stockholm.
  • C. Maarkedal
    Maarkedal is a rural municipality in the Flemish Ardennes of East Flanders, Belgium, known for its hilly landscape and cycling routes.
  • D. Hörby
    Hörby is a small municipality in southern Sweden’s Skåne County, known for its rural landscape and traditional Swedish town character.
  • E. Sundbyvester
    Sundbyvester is a district of Copenhagen located on Amager Island, known primarily as a residential urban area.
  • 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.