Triple

T1876349
Position Surface form Disambiguated ID Type / Status
Subject Kaag en Braassem E39152 entity
Predicate contains P35 FINISHED
Object Kagerplassen E151655 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: Kagerplassen | Statement: [Kaag en Braassem, contains, Kagerplassen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kagerplassen
Context triple: [Kaag en Braassem, contains, Kagerplassen]
  • A. Kagerplassen chosen
    Kagerplassen is a lake and recreational water area in South Holland, Netherlands, popular for boating, sailing, and watersports amid a landscape of polders and windmills.
  • B. Kjelsås
    Kjelsås is a residential neighborhood in northern Oslo, Norway, known for its hilly terrain, proximity to Marka forest, and access to the city via tram and rail connections.
  • C. Frognerseteren
    Frognerseteren is a hilltop area in Oslo, Norway, known for its panoramic views over the city, traditional wooden restaurant, and access to popular hiking and skiing trails.
  • D. Kongsseteren
    Kongsseteren is a historic winter residence and retreat used by the Norwegian royal family near Oslo.
  • E. Näsbypark
    Näsbypark is a residential suburban district in the northern Stockholm area of Sweden, known for its villas, green spaces, and coastal location by 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_69a8862f7074819096afe7fe65e179e9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0d902ac8190a2d9bb6f683986e4 completed March 7, 2026, 5 a.m.
NED1 Entity disambiguation (via context triple) batch_69addf56e2748190a2044d33d29d8324 completed March 8, 2026, 8:43 p.m.
Created at: March 4, 2026, 7:34 p.m.