Triple

T3676151
Position Surface form Disambiguated ID Type / Status
Subject Djurgården E77996 entity
Predicate contains P35 FINISHED
Object Skansen E80003 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: Skansen | Statement: [Djurgården, contains, Skansen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skansen
Context triple: [Djurgården, contains, Skansen]
  • A. Skansen chosen
    Skansen is an open-air museum and zoo in Stockholm that showcases traditional Swedish culture, architecture, and wildlife.
  • B. Kronobergsparken
    Kronobergsparken is a large, hilly public park in the Kungsholmen district of central Stockholm, known for its green spaces, playgrounds, and views over the city.
  • C. Odense Zoo
    Odense Zoo is a popular Danish zoological garden in the city of Odense, known for its diverse animal collections and family-friendly exhibits.
  • D. Kristineberg
    Kristineberg is a residential neighborhood in the western part of central Stockholm, known for its waterfront location and green areas.
  • E. Tivoli Gardens
    Tivoli Gardens is a historic amusement park and pleasure garden in central Copenhagen, renowned for its charming rides, landscaped gardens, and cultural events.
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc462ffdc8190896e9f98f648e2f3 completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48856b7d481909d9cc32586d61d44 completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:25 p.m.