Triple
T11600295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krasnogorsk Urban Okrug |
E275110
|
entity |
| Predicate | hasJurisdictionOver |
P808
|
FINISHED |
| Object | Krasnogorsk |
E112823
|
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: Krasnogorsk | Statement: [Krasnogorsk Urban Okrug, hasJurisdictionOver, Krasnogorsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krasnogorsk Context triple: [Krasnogorsk Urban Okrug, hasJurisdictionOver, Krasnogorsk]
-
A.
Krasnogorsk
chosen
Krasnogorsk is a city in western Russia that serves as an important administrative and residential center just outside Moscow.
-
B.
Krasnokokshaysk
Krasnokokshaysk is the former name of the city now known as Yoshkar-Ola, the capital of the Mari El Republic in Russia.
-
C.
Konakovo
Konakovo is a town in Tver Oblast, Russia, situated on the Volga River and known for its power station and riverside recreation.
-
D.
Krasnokamsk
Krasnokamsk is an industrial city in western Russia known for its paper, printing, and chemical industries.
-
E.
Makeyevka
Makeyevka is an industrial city in eastern Ukraine’s Donetsk Oblast, historically known for its coal mining and metallurgical industries.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8954c3c248190bcccd4c7ff667b3a |
completed | April 10, 2026, 6:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f12fefffa88190b4aa484b6bc4eb17 |
completed | April 28, 2026, 10:08 p.m. |
Created at: April 8, 2026, 9:38 p.m.