Triple

T16490643
Position Surface form Disambiguated ID Type / Status
Subject Greenland Provincial Council E400557 entity
Predicate seat P75 FINISHED
Object Nuuk E92187 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: Nuuk | Statement: [Greenland Provincial Council, seat, Nuuk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nuuk
Context triple: [Greenland Provincial Council, seat, Nuuk]
  • A. Nuuk chosen
    Nuuk is the largest city in Greenland, serving as its cultural and economic center on the country's southwest coast.
  • B. Gjoa Haven
    Gjoa Haven is a small Inuit community in Nunavut, Canada, known as a historic Arctic settlement linked to polar exploration and the Northwest Passage.
  • C. Nuuk Airport
    Nuuk Airport is the main domestic and regional airport serving Greenland’s capital, providing vital air connections within the country and to select international destinations.
  • D. Longyearbyen
    Longyearbyen is the world’s northernmost permanent settlement and the largest town in the Norwegian Arctic archipelago of Svalbard.
  • E. Karasjok
    Karasjok is a municipality in northern Norway known as a cultural and political center for the Sámi people.
  • 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e2f31f48190825af5934d976ab7 completed April 18, 2026, 7:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00607cbc80819088505d8bdd663109 completed May 10, 2026, 10:39 a.m.
Created at: April 10, 2026, 5:13 a.m.