Triple

T594556
Position Surface form Disambiguated ID Type / Status
Subject Northern Norway E17350 entity
Predicate majorTown P316 FINISHED
Object Kirkenes
Kirkenes is a remote Arctic town in northeastern Norway, near the Russian border, known for its Barents Sea port, winter tourism, and role as a gateway to the far north.
 E95872 NE FINISHED

How this triple was built (4 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: Kirkenes | Statement: [Northern Norway, majorTown, Kirkenes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kirkenes
Context triple: [Northern Norway, majorTown, Kirkenes]
  • 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. Muroran
    Muroran is an industrial port city in southern Hokkaido, Japan, known for its steel industry and scenic coastal landscapes.
  • C. Bodø
    Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
  • D. Vyborg
    Vyborg is a historic port city in northwestern Russia near the Finnish border, known for its medieval castle and long-contested status between Sweden, Finland, and Russia.
  • E. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kirkenes
Triple: [Northern Norway, majorTown, Kirkenes]
Generated description
Kirkenes is a remote Arctic town in northeastern Norway, near the Russian border, known for its Barents Sea port, winter tourism, and role as a gateway to the far north.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kirkenes
Target entity description: Kirkenes is a remote Arctic town in northeastern Norway, near the Russian border, known for its Barents Sea port, winter tourism, and role as a gateway to the far north.
  • 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. Muroran
    Muroran is an industrial port city in southern Hokkaido, Japan, known for its steel industry and scenic coastal landscapes.
  • C. Bodø
    Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
  • D. Vyborg
    Vyborg is a historic port city in northwestern Russia near the Finnish border, known for its medieval castle and long-contested status between Sweden, Finland, and Russia.
  • E. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • F. None of above. chosen

Provenance (5 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_69a49379d09c8190ac7e00b24e2810b1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49bd15c5881909b59ed4c88687e7b completed March 1, 2026, 8:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d69ade481909322f5f28f0050e4 completed March 3, 2026, 11:23 p.m.
NEDg Description generation batch_69a78257f9988190a04b8d764d820194 completed March 4, 2026, 12:52 a.m.
NED2 Entity disambiguation (via description) batch_69a78337cd4c8190bce8a0716a6e85e4 completed March 4, 2026, 12:56 a.m.
Created at: March 1, 2026, 7:33 p.m.