Triple

T1014407
Position Surface form Disambiguated ID Type / Status
Subject Haninge Municipality E21897 entity
Predicate hasIsland P970 FINISHED
Object Utö E125581 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: Utö | Statement: [Haninge Municipality, hasIsland, Utö]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Utö
Context triple: [Haninge Municipality, hasIsland, Utö]
  • A. Utö chosen
    Utö is a Swedish island in the Stockholm archipelago known for its historic iron ore mines, scenic nature, and popular summer tourism.
  • B. Lidingö
    Lidingö is a suburban island town in the Stockholm archipelago known for its affluent residential areas, natural landscapes, and proximity to Sweden’s capital.
  • C. Ornö
    Ornö is a large island in the Stockholm archipelago of Sweden, known for its forests, bays, and traditional summer cottages.
  • D. Öland
    Öland is Sweden’s second-largest island, known for its unique limestone plains, rich birdlife, and popular summer tourism along the Baltic Sea coast.
  • E. Södertörn
    Södertörn is a large peninsula in eastern Sweden, south of Stockholm, known for its mix of suburban areas, forests, and coastline along the Baltic Sea.
  • 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_69a493c68e24819080ed0ee8bcfd5ce0 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7be907c8190b5c6ea89257755a7 completed March 1, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac59978cb4819098118b6348b8a55a completed March 7, 2026, 5 p.m.
Created at: March 1, 2026, 7:41 p.m.