Triple

T3522192
Position Surface form Disambiguated ID Type / Status
Subject Kven people E74447 entity
Predicate primaryLocation P3231 FINISHED
Object Troms E80793 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: Troms | Statement: [Kven people, primaryLocation, Troms]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Troms
Context triple: [Kven people, primaryLocation, Troms]
  • A. Troms chosen
    Troms was a former county in northern Norway known for its Arctic landscapes, coastal fjords, and the city of Tromsø.
  • B. Tjøme
    Tjøme is a scenic island and former municipality in Vestfold, Norway, known for its coastal landscapes, summer cabins, and popular seaside recreation areas.
  • C. Røst
    Røst is a small, remote island and fishing community in northern Norway, known for its dramatic coastal scenery, rich seabird colonies, and traditional cod fisheries.
  • D. Bojnord
    Bojnord is a city in northeastern Iran that serves as the capital of North Khorasan Province.
  • E. Finnsnes
    Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
  • 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_69ad85d0c5488190a3d8e02ebd01a1aa completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc4dd6d48190a5a3f4b86c82b86c completed March 8, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38bca41a88190b5550b9c1e763092 completed March 13, 2026, 4 a.m.
Created at: March 8, 2026, 3:19 p.m.