Triple

T16197002
Position Surface form Disambiguated ID Type / Status
Subject Hotel Union Øye E393086 entity
Predicate locatedIn P40 FINISHED
Object Øye NE NERFINISHED

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: Øye | Statement: [Hotel Union Øye, locatedIn, Øye]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Øye
Context triple: [Hotel Union Øye, locatedIn, Øye]
  • A. Øye chosen
    Øye is a small Norwegian village in the Sunnmøre region, known for its dramatic fjord landscape and the historic Hotel Union Øye.
  • B. Andøya
    Andøya is a large Norwegian island in Nordland county, known for its dramatic coastal landscapes, space center, and rich bird and whale-watching opportunities.
  • C. Sørøya
    Sørøya is a large, sparsely populated island in northern Norway known for its rugged coastal landscapes, rich fishing grounds, and opportunities for outdoor activities such as hiking and sea angling.
  • D. Askøy island
    Askøy island is a large Norwegian island in Vestland county, known for its coastal landscapes and proximity to the city of Bergen.
  • E. Edgeøya
    Edgeøya is one of the large, remote islands in the Svalbard archipelago of Arctic Norway, known for its rugged tundra landscape and rich polar wildlife.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222dace848190b1a98e47333b922b completed April 17, 2026, 12:08 p.m.
Created at: April 10, 2026, 5:02 a.m.