Triple

T7163041
Position Surface form Disambiguated ID Type / Status
Subject Rindö E166993 entity
Predicate hasSettlement P1068 FINISHED
Object Rindöby E166993 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: Rindöby | Statement: [Rindö, hasSettlement, Rindöby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rindöby
Context triple: [Rindö, hasSettlement, Rindöby]
  • A. Vårby
    Vårby is a suburban district in the southern Stockholm area of Sweden, known for its residential neighborhoods and proximity to Lake Mälaren.
  • B. Rindö chosen
    Rindö is an island in Sweden’s Stockholm archipelago, known for its coastal scenery and strategic location near the town of Vaxholm.
  • C. 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.
  • D. Hörby
    Hörby is a small municipality in southern Sweden’s Skåne County, known for its rural landscape and traditional Swedish town character.
  • E. Korsnäs
    Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
  • 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_69c68888c10c819095e0383020225758 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e82feee481908fa180ea8c9924fa completed March 27, 2026, 8:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7adc8b06c81909791e38becb594f6 completed March 28, 2026, 10:30 a.m.
Created at: March 27, 2026, 2:47 p.m.