Triple

T20053314
Position Surface form Disambiguated ID Type / Status
Subject Ørland Airport E499259 entity
Predicate cityServed P82 FINISHED
Object Ørland 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: Ørland | Statement: [Ørland Airport, cityServed, Ørland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ørland
Context triple: [Ørland Airport, cityServed, Ørland]
  • A. Ørland chosen
    Ørland is a coastal municipality in Trøndelag county, Norway, known for its strategic air base and rich maritime and agricultural landscape.
  • B. Ørje
    Ørje is a small village in southeastern Norway known for its historic locks on the Halden Canal and its role as a local commercial and service hub.
  • C. Røst
    Røst is a small, remote island and fishing community in northern Norway, known for its dramatic coastal scenery, rich seabird colonies, and traditional cod fisheries.
  • D. 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.
  • E. Turøy
    Turøy is a small island in Western Norway known for its coastal scenery, birdlife, and proximity to the city of Bergen.
  • 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6633043a481908359ad232607182a completed April 20, 2026, 5:32 p.m.
Created at: April 11, 2026, 3:38 p.m.