Triple

T23202937
Position Surface form Disambiguated ID Type / Status
Subject Vágar Airport E580367 entity
Predicate cityServed P82 FINISHED
Object Tórshavn 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: Tórshavn | Statement: [Vágar Airport, cityServed, Tórshavn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tórshavn
Context triple: [Vágar Airport, cityServed, Tórshavn]
  • A. Tórshavn chosen
    Tórshavn is the capital and largest city of the Faroe Islands, serving as the political, cultural, and economic center of the archipelago.
  • B. Havnor
    Havnor is the central island and political heart of Earthsea, home to its capital city and the seat of the Archipelago’s rulers in Ursula K. Le Guin’s fantasy series.
  • C. Mariehamn
    Mariehamn is the main town and administrative, cultural, and economic center of the autonomous Åland Islands in the Baltic Sea.
  • D. Klaksvík
    Klaksvík is the second-largest town in the Faroe Islands, known as an important fishing and commercial center located on the island of Borðoy.
  • E. Faro
    Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
  • 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_69e24602ae1481908aaa6bc7ca493867 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1907a8bb48190846802a24d33bccf completed April 29, 2026, 5 a.m.
Created at: April 17, 2026, 4:07 p.m.