Triple

T4587939
Position Surface form Disambiguated ID Type / Status
Subject Innherred E103413 entity
Predicate contains P35 FINISHED
Object Inderøy E132741 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: Inderøy | Statement: [Innherred, contains, Inderøy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inderøy
Context triple: [Innherred, contains, Inderøy]
  • A. Inderøy chosen
    Inderøy is a rural municipality in central Norway known for its cultural heritage, agricultural landscape, and scenic location along the Trondheimsfjord.
  • B. Nøtterøy
    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.
  • C. 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.
  • D. Skjervøy
    Skjervøy is a coastal fishing town and island community in northern Norway, known for its Arctic scenery and rich marine life.
  • E. Lauvøy
    Lauvøy is an island that forms part of the Finnøy area in Norway, known for its coastal landscape and maritime surroundings.
  • 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_69bd43dccaf08190aa89e9991a289719 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd591fc20481908d8d4b71d055ae8c completed March 20, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69bde0b1b014819085543bd297f925c1 completed March 21, 2026, 12:05 a.m.
Created at: March 20, 2026, 1:11 p.m.