Triple

T4990567
Position Surface form Disambiguated ID Type / Status
Subject Tønsberg E112118 entity
Predicate hasNearbyIsland P970 FINISHED
Object Nøtterøy E194555 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: Nøtterøy | Statement: [Tønsberg, hasNearbyIsland, Nøtterøy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nøtterøy
Context triple: [Tønsberg, hasNearbyIsland, Nøtterøy]
  • A. Nøtterøy chosen
    Nøtterøy is a large, populated island and former municipality in Vestfold, Norway, situated in the Oslofjord and known for its coastal landscapes and residential communities.
  • B. Askøy
    Askøy is a large island and municipality on Norway’s west coast, situated near Bergen and known for its coastal landscapes and commuter links to the city.
  • C. Inderøy
    Inderøy is a rural municipality in central Norway known for its cultural heritage, agricultural landscape, and scenic location along the Trondheimsfjord.
  • D. Skjervøy
    Skjervøy is a coastal fishing town and island community in northern Norway, known for its Arctic scenery and rich marine life.
  • E. Rennesøy
    Rennesøy is an island and former municipality in Rogaland county, southwestern Norway, known for its coastal landscape and proximity to the city of Stavanger.
  • 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_69bd441be7bc8190b530362d427b97d2 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd728141d48190a0713e6d33c50fb6 completed March 20, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea470ca3c81909e24b18e1e609dbd completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:34 p.m.