Triple
T18208764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lamaria Church |
E435973
|
entity |
| Predicate | proximityTo |
P350
|
FINISHED |
| Object | Mestia |
—
|
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: Mestia | Statement: [Lamaria Church, proximityTo, Mestia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mestia Context triple: [Lamaria Church, proximityTo, Mestia]
-
A.
Mestia
chosen
Mestia is a highland town in northwestern Georgia, renowned as a cultural and tourist hub of the Svaneti region in the Caucasus Mountains.
-
B.
Gandzhachay
Gandzhachay is a river in western Azerbaijan that flows through the city of Ganja before joining the Kura River.
-
C.
Akhalkalaki
Akhalkalaki is a town in southern Georgia known as a regional center in the Samtskhe–Javakheti area, historically significant and situated near the country’s border with Armenia.
-
D.
Abastumani
Abastumani is a small resort town in southern Georgia, historically known for its mountain climate and therapeutic sanatoriums.
-
E.
Yeghvard
Yeghvard is a town in Armenia known for its historic churches and location within the central Kotayk Province.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e2261a848190b62a8485009f8f38 |
completed | April 19, 2026, 2:09 p.m. |
Created at: April 10, 2026, 10:32 a.m.