Triple

T8649298
Position Surface form Disambiguated ID Type / Status
Subject Kaag E205057 entity
Predicate surroundedBy P224 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, surroundedBy, Kagerplassen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kagerplassen
Context triple: [Kaag, surroundedBy, 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. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • E. Grebbestad
    Grebbestad is a coastal fishing village and popular tourist destination in Tanum Municipality on Sweden’s west coast, known for its seafood and picturesque archipelago.
  • 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_69ca834e56848190abb0eeaec9dedd32 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4813d0548190b203e594acc38c8f completed March 31, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ceccc166548190a1dd706041e4bfa2 completed April 2, 2026, 8:08 p.m.
Created at: March 30, 2026, 6:29 p.m.