Triple

T11021213
Position Surface form Disambiguated ID Type / Status
Subject Tromsø Airport, Langnes E260491 entity
Predicate servesRegion P82 FINISHED
Object Troms E80793 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: Troms | Statement: [Tromsø Airport, Langnes, servesRegion, Troms]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Troms
Context triple: [Tromsø Airport, Langnes, servesRegion, Troms]
  • A. Troms chosen
    Troms was a former county in northern Norway known for its Arctic landscapes, coastal fjords, and the city of Tromsø.
  • B. Trondenes
    Trondenes is a historic former municipality and parish in northern Norway, known for its medieval stone church and role as an administrative center in the Harstad region.
  • C. Tjørhom
    Tjørhom is a small village in southwestern Norway known for its mountainous landscape and proximity to popular skiing and outdoor recreation areas.
  • D. Tjuneroy
    Tjuneroy was an ancient Egyptian official, likely a high-ranking scribe or priest under Ramesses II, associated with the creation of the Saqqara King List.
  • E. Bjerke
    Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797bb6eec81909d8004af31f307f7 completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e374f64b3c8190b0b55193f81d3bc5 completed April 18, 2026, 12:11 p.m.
Created at: April 8, 2026, 9:25 p.m.