Triple
T12722375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramenskoye airfield |
E304016
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Ramenskoye |
E221644
|
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: Ramenskoye | Statement: [Ramenskoye airfield, nearbyCity, Ramenskoye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ramenskoye Context triple: [Ramenskoye airfield, nearbyCity, Ramenskoye]
-
A.
Ramenskoye
chosen
Ramenskoye is a town in Moscow Oblast, Russia, located southeast of Moscow and known for its industrial base and proximity to major Moscow airports.
-
B.
Nikolskoye
Nikolskoye is the main and only permanent settlement on Russia’s remote Commander Islands in the Bering Sea.
-
C.
Nikolskoye
Nikolskoye is a town in northwestern Russia known as part of the Saint Petersburg metropolitan area in Leningrad Oblast.
-
D.
Petrovskoye
Petrovskoye was the original Russian fortress settlement that later developed into the modern city of Makhachkala in Dagestan, Russia.
-
E.
Rybatskoye
Rybatskoye is a metro station in Saint Petersburg, Russia, serving as the eastern terminus of one of the city’s metro lines.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d964133fe481909a44b8159ab8997b |
completed | April 10, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5b9e0c4819095194dc42677e17f |
completed | May 3, 2026, 7:14 a.m. |
Created at: April 9, 2026, 5:24 p.m.