Triple

T924029
Position Surface form Disambiguated ID Type / Status
Subject Lidingö Municipality E19943 entity
Predicate administrativeCenter P1474 FINISHED
Object Lidingö E109113 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: Lidingö | Statement: [Lidingö Municipality, administrativeCenter, Lidingö]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lidingö
Context triple: [Lidingö Municipality, administrativeCenter, Lidingö]
  • A. Lidingö chosen
    Lidingö is a suburban island town in the Stockholm archipelago known for its affluent residential areas, natural landscapes, and proximity to Sweden’s capital.
  • B. 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.
  • C. Bømlo
    Bømlo is a large island and municipality in Vestland county, Norway, known for its rugged coastline, fishing communities, and extensive network of tunnels and bridges connecting it to the mainland.
  • D. Gotland
    Gotland is Sweden’s largest island, located in the Baltic Sea and known for its medieval town of Visby, limestone cliffs, and rich Viking-era history.
  • E. Bornholm
    Bornholm is a Danish island known for its rocky coastline, medieval ruins, and picturesque fishing villages in 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_69a493a099788190a696d9d8408cbaf4 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3296f50819087f809fbe90b139e completed March 1, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7ee094c94819093578c949db7ded9 completed March 4, 2026, 8:32 a.m.
Created at: March 1, 2026, 7:40 p.m.