Triple

T15216007
Position Surface form Disambiguated ID Type / Status
Subject Kola Bay E363637 entity
Predicate hasCityOnShore P969 FINISHED
Object Polyarny E381371 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: Polyarny | Statement: [Kola Bay, hasCityOnShore, Polyarny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Polyarny
Context triple: [Kola Bay, hasCityOnShore, Polyarny]
  • A. Polyarny chosen
    Polyarny is a Russian naval town in Murmansk Oblast known as a key base for the Northern Fleet and submarine operations in the Arctic region.
  • B. Polar
    Polar is a 2019 action-thriller film directed by Jonas Åkerlund, based on the Dark Horse graphic novel about an aging assassin forced out of retirement.
  • C. Polar
    Polar is a record label associated with the Swedish company Polar Music, known for releasing music by prominent Scandinavian artists.
  • D. Polar
    Polar is a small, friendly polar bear character and playable racer in the Crash Bandicoot kart-racing games.
  • E. Polar
    Polar was a NASA scientific research satellite dedicated to studying Earth's polar magnetosphere and auroral phenomena as part of the International Solar–Terrestrial Physics program.
  • 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_69e0076e4348819091fa91c1562e7c5c 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.