Triple
T19461424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borjomi Central Park |
E486880
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Borjomi |
—
|
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: Borjomi | Statement: [Borjomi Central Park, locatedIn, Borjomi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Borjomi Context triple: [Borjomi Central Park, locatedIn, Borjomi]
-
A.
Borjomi
chosen
Borjomi is a Georgian resort town famous for its mineral water springs and scenic location in the Borjomi Gorge.
-
B.
Tskaltubo
Tskaltubo is a spa town in western Georgia renowned for its radon-carbonate mineral springs and Soviet-era sanatoriums.
-
C.
Bolnisi
Bolnisi is a town in southern Georgia known for its historic Bolnisi Sioni Cathedral and its diverse cultural heritage.
-
D.
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.
-
E.
Gudauri
Gudauri is a popular ski resort town in the Greater Caucasus Mountains of Georgia, known for its high-altitude slopes and freeride opportunities.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c983f481908b2684dc4380b889 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:38 p.m.