Triple

T14376857
Position Surface form Disambiguated ID Type / Status
Subject Tórshavn E356497 entity
Predicate locatedIn P40 FINISHED
Object Streymoy E143905 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: Streymoy | Statement: [Tórshavn, locatedIn, Streymoy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Streymoy
Context triple: [Tórshavn, locatedIn, Streymoy]
  • A. Streymoy chosen
    Streymoy is the largest and most populous island of the Faroe Islands, home to the capital city Tórshavn and the archipelago’s main political and economic activities.
  • B. Suðuroy
    Suðuroy is the southernmost of the Faroe Islands, known for its dramatic coastal cliffs, small fishing villages, and relatively remote, rugged landscape.
  • C. Eysturoy
    Eysturoy is the second-largest island of the Faroe Islands, known for its rugged mountains, fjords, and traditional fishing villages.
  • D. Ærø
    Ærø is a small Danish island in the Baltic Sea known for its picturesque coastal towns, historic architecture, and popular cycling and sailing routes.
  • E. Rømø
    Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900949fc81909be0da1734c46645 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c5728fc819089ef3c7c34b10101 completed May 8, 2026, 2:37 a.m.
Created at: April 10, 2026, 1:16 a.m.