Triple
T7513717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ust-Dzheguta |
E177587
|
entity |
| Predicate | nearestMajorCity |
P1982
|
FINISHED |
| Object | Cherkessk |
E211161
|
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: Cherkessk | Statement: [Ust-Dzheguta, nearestMajorCity, Cherkessk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cherkessk Context triple: [Ust-Dzheguta, nearestMajorCity, Cherkessk]
-
A.
Cherkessk
chosen
Cherkessk is a city in southwestern Russia that serves as the administrative, economic, and cultural center of the Karachay-Cherkess Republic in the North Caucasus.
-
B.
Karachayevsk
Karachayevsk is a town in southwestern Russia located in the North Caucasus region, serving as one of the main urban centers of the Karachay-Cherkess Republic.
-
C.
Kamyshin
Kamyshin is a significant industrial and river port city on the Volga River in southwestern Russia.
-
D.
Kizlyar
Kizlyar is a town in the Republic of Dagestan, Russia, known historically as a frontier settlement and trading center in the North Caucasus region.
-
E.
Kislovodsk
Kislovodsk is a Russian spa and resort city in the North Caucasus, renowned for its mineral springs and mountainous surroundings.
- 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_69c69f2891148190a484f3b8222c6f1b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5d6ccb08190a568a9b58bfbd0cc |
completed | March 27, 2026, 9:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84619aac8819083a1d7380f4b30d3 |
completed | March 28, 2026, 9:20 p.m. |
Created at: March 27, 2026, 3:45 p.m.