Triple
T17639543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tskaltubo Municipality |
E429186
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Tskaltubo |
—
|
NE NERFINISHED |
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: Tskaltubo | Statement: [Tskaltubo Municipality, contains, Tskaltubo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tskaltubo Context triple: [Tskaltubo Municipality, contains, Tskaltubo]
-
A.
Tskaltubo
chosen
Tskaltubo is a spa town in western Georgia renowned for its radon-carbonate mineral springs and Soviet-era sanatoriums.
-
B.
Borjomi
Borjomi is a Georgian resort town famous for its mineral water springs and scenic location in the Borjomi Gorge.
-
C.
Pyatigorsk
Pyatigorsk is a historic spa and resort city in southern Russia, known for its mineral springs and location in the North Caucasus region.
-
D.
Gudermes
Gudermes is a town in the Chechen Republic of Russia that serves as an important regional transport and administrative center.
-
E.
Mineralnye Vody
Mineralnye Vody is a town in Russia’s Stavropol Krai known as a key transport hub in the North Caucasus, particularly for its railway and airport connections.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46de3f2a08190998641fa589bad78 |
completed | April 19, 2026, 5:53 a.m. |
Created at: April 10, 2026, 6:01 a.m.