Triple
T8761904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kislovodsk |
E208221
|
entity |
| Predicate | nearbyCities |
P3883
|
FINISHED |
| Object | Zheleznovodsk |
E641383
|
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: Zheleznovodsk | Statement: [Kislovodsk, nearbyCities, Zheleznovodsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zheleznovodsk Context triple: [Kislovodsk, nearbyCities, Zheleznovodsk]
-
A.
Zheleznovodsk
chosen
Zheleznovodsk is a spa town in Russia’s Stavropol Krai, known for its mineral springs and health resorts in the Caucasus region.
-
B.
Novocherkassk
Novocherkassk is a historic city in Russia’s Rostov Oblast that served as a key Cossack and military administrative center.
-
C.
Volgodonsk
Volgodonsk is an industrial city in southwestern Russia known for its nuclear power plant and location on the Tsimlyansk Reservoir in Rostov Oblast.
-
D.
Gelendzhik
Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
-
E.
Zhigulevsk
Zhigulevsk is an industrial city in Russia located on the Volga River, known for its proximity to the Zhiguli Mountains and the Zhiguli Hydroelectric Station.
- 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5dfa9d6c81908c4c6b3a6f84f67d |
completed | March 31, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdb7b08488190ba276e7b665e3ea4 |
completed | April 3, 2026, 3:23 p.m. |
Created at: March 30, 2026, 6:40 p.m.