Triple

T15216151
Position Surface form Disambiguated ID Type / Status
Subject Barents Sea coast E363640 entity
Predicate hasPort P35 FINISHED
Object Kirkenes E95872 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: Kirkenes | Statement: [Barents Sea coast, hasPort, Kirkenes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kirkenes
Context triple: [Barents Sea coast, hasPort, Kirkenes]
  • A. Kirkenes chosen
    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.
  • B. Murmansk
    Murmansk is a major Arctic port city in northwestern Russia, known for its ice-free harbor and strategic military and shipping importance.
  • C. Vardø
    Vardø is a small coastal town in Norway’s far northeast, known as one of the country’s easternmost settlements and a historic Arctic gateway.
  • D. Severodvinsk
    Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076f90c481909989befe031a2cae completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed343f51481908f04c35d37b39ad2 completed May 9, 2026, 6:25 a.m.
Created at: April 10, 2026, 3:11 a.m.