Triple

T1231545
Position Surface form Disambiguated ID Type / Status
Subject Faroe Islands E26453 entity
Predicate largestCity P235 FINISHED
Object Tórshavn E140586 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: Tórshavn | Statement: [Faroe Islands, largestCity, Tórshavn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tórshavn
Context triple: [Faroe Islands, largestCity, Tórshavn]
  • A. Mariehamn
    Mariehamn is the main town and administrative, cultural, and economic center of the autonomous Åland Islands in the Baltic Sea.
  • B. 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.
  • C. Port of Tórshavn chosen
    The Port of Tórshavn is the principal maritime hub and commercial harbor of the Faroe Islands, serving as a key center for fishing, cargo, and passenger traffic in the North Atlantic.
  • D. Køpmannæhafn
    Køpmannæhafn is the historical Danish name for the city now known as Copenhagen, reflecting its origins as a merchant harbor.
  • E. Fredericia
    Fredericia is a Danish coastal town in Jutland known for its historic 17th-century fortress and well-preserved ramparts.
  • 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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be5a25348190a0665b6324c4d8f5 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69aca2eb158081909f1175d8f4daaa96 completed March 7, 2026, 10:12 p.m.
Created at: March 1, 2026, 7:47 p.m.