Triple

T5571613
Position Surface form Disambiguated ID Type / Status
Subject Longyearbyen E146214 entity
Predicate formerName P65 FINISHED
Object Longyear City E146214 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: Longyear City | Statement: [Longyearbyen, formerName, Longyear City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Longyear City
Context triple: [Longyearbyen, formerName, Longyear City]
  • A. Narvik
    Narvik is a port town in northern Norway known for its strategic importance during World War II and as the site of major naval and land battles.
  • B. Kiruna
    Kiruna is a mining town in northern Sweden known for its large iron ore mine and its location above the Arctic Circle.
  • C. Selkirk
    Selkirk is a historic town in the Scottish Borders known for its legal heritage, including past judicial functions and associations with Scotland’s justice system.
  • D. Hydaburg
    Hydaburg is a small city on Prince of Wales Island in Alaska known as a central community for the Haida people and their culture.
  • E. Longyearbyen chosen
    Longyearbyen is the world’s northernmost permanent settlement and the largest town in the Norwegian Arctic archipelago of Svalbard.
  • 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_69c008ffed108190a084602227af6157 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020518f348190879ac67dab307134 completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0284ef6e48190bae9c9a1b1d77f5d completed March 22, 2026, 5:35 p.m.
Created at: March 22, 2026, 3:37 p.m.