Triple
T1231493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grozny |
E26451
|
entity |
| Predicate | locatedInMountainRangeRegion |
P24755
|
FINISHED |
| Object | Caucasus region |
—
|
LITERAL 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: Caucasus region | Statement: [Grozny, locatedInMountainRangeRegion, Caucasus region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInMountainRangeRegion Context triple: [Grozny, locatedInMountainRangeRegion, Caucasus region]
-
A.
locatedInMountain
Indicates that something is situated within, on, or as part of a mountain.
-
B.
hasMountainRange
Indicates that one entity possesses, contains, or is geographically associated with a specific mountain range.
-
C.
hasMountain
Indicates that a location or region possesses or contains at least one mountain.
-
D.
mountainRange
Indicates that one entity is a mountain range that the other entity is part of, associated with, or located in.
-
E.
sourceMountainRange
Indicates that a river, stream, or similar feature originates from or has its source in a specified mountain range.
- F. None of above. chosen
Provenance (4 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be5a25348190a0665b6324c4d8f5 |
completed | March 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69a4bb65d61c8190bf0424ea0019a98b |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bbf83584819088c69366f58586cc |
completed | March 1, 2026, 10:21 p.m. |
Created at: March 1, 2026, 7:47 p.m.