Triple
T16289757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | statue of Lenin at Khimki Reservoir |
E395487
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Khimki |
E52717
|
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: Khimki | Statement: [statue of Lenin at Khimki Reservoir, locatedNear, Khimki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khimki Context triple: [statue of Lenin at Khimki Reservoir, locatedNear, Khimki]
-
A.
Khimki
chosen
Khimki is a city in Moscow Oblast, Russia, forming part of the Moscow metropolitan area and known for its proximity to major transport hubs and industrial facilities.
-
B.
Pirogovo
Pirogovo is a settlement located near the Pirogovskoye Reservoir, known as a local residential and recreational area.
-
C.
Sokolka
Sokolka is a town in present-day northeastern Poland, historically part of the Grodno region, known for its multicultural heritage and role as a local administrative and trade center.
-
D.
Krylatskoye
Krylatskoye is a Moscow Metro station serving the Krylatskoye District in western Moscow, Russia.
-
E.
Kireyevsk
Kireyevsk is a small industrial town in western Russia known for its coal-mining history and location within the Tula region.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e249175e24819082e571039e278056 |
completed | April 17, 2026, 2:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004571013c8190ae3e4ecd17c08004 |
completed | May 10, 2026, 8:44 a.m. |
Created at: April 10, 2026, 5:05 a.m.