Triple
T15732222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polyarny |
E381371
|
entity |
| Predicate | renamedTo |
P3432
|
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: [Polyarny, renamedTo, Polyarny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Polyarny Context triple: [Polyarny, renamedTo, 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fd3614481908b2694b1d3550058 |
completed | April 16, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff82fed7888190b45f28ac91e0079e |
completed | May 9, 2026, 6:54 p.m. |
Created at: April 10, 2026, 4:46 a.m.