Triple
T19925643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Severomorsk-2 air base |
E478914
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Severomorsk |
—
|
NE NERFINISHED |
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: Severomorsk | Statement: [Severomorsk-2 air base, locatedNear, Severomorsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Severomorsk Context triple: [Severomorsk-2 air base, locatedNear, Severomorsk]
-
A.
Severomorsk
chosen
Severomorsk is a closed naval town in Russia’s Murmansk Oblast that serves as the main base of the Russian (formerly Soviet) Northern Fleet on the Barents Sea.
-
B.
Sestroretsk
Sestroretsk is a town in northwestern Russia, now part of Saint Petersburg, historically known for its arms factory and seaside resort area on the Gulf of Finland.
-
C.
Severodvinsk
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
-
D.
Tuapse
Tuapse is a Black Sea port town in southern Russia known as a seaside resort and industrial center within Krasnodar Krai.
-
E.
Krasnoufimsk
Krasnoufimsk is a small historic town in Russia’s Ural region, known for its traditional architecture and role as a local administrative and cultural center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659c992fc8190bd262d528be0e636 |
completed | April 20, 2026, 4:52 p.m. |
Created at: April 10, 2026, 1:53 p.m.