Triple

T6273104
Position Surface form Disambiguated ID Type / Status
Subject Vágar Airport E140585 entity
Predicate serves city P3936 FINISHED
Object Tórshavn E356497 NE FINISHED

How this triple was built (3 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, serves city, Tórshavn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tórshavn
Context triple: [Vágar Airport, serves city, 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. Mariehamn
    Mariehamn is the main town and administrative, cultural, and economic center of the autonomous Åland Islands in the Baltic Sea.
  • C. 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.
  • D. Faaborg
    Faaborg is a historic coastal town on the island of Funen in southern Denmark, known for its well-preserved old town, harbor, and cultural attractions.
  • E. Hirtshals
    Hirtshals is a Danish coastal town in northern Jutland known for its busy fishing and ferry port on the Skagerrak and its role as a key transport hub between Denmark and Norway.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: serves city
Context triple: [Vágar Airport, serves city, Tórshavn]
  • A. servedCity chosen
    Indicates that a service, route, or facility operates in, reaches, or is available to a particular city.
  • B. cityServedType
    Indicates the type or category of city that is served by a given entity (such as a facility, service, or infrastructure).
  • C. servesOn
    Indicates that one entity performs duties, functions, or holds a role as a member within another entity, such as a group, body, or organization.
  • D. servesCapitalCityOf
    Indicates that one entity functions as the capital city for another entity (typically a country, state, or region).
  • E. servesCitizensOf
    Indicates that an entity provides services, support, or functions on behalf of the citizens of a specified place or jurisdiction.
  • F. None of above.

Provenance (4 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_69c008cc158881908df6ec94a911c736 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063be5a148190a8752426d2d220f8 completed March 22, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62d1f28748190a62fc26f92f0c15f completed March 27, 2026, 7:09 a.m.
PD Predicate disambiguation batch_69c05606fb50819082d1a5a91e5030b6 completed March 22, 2026, 8:50 p.m.
Created at: March 22, 2026, 4:25 p.m.