Triple
T3180895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Caucasian Federal District |
E66581
|
entity |
| Predicate | hasMountainousTerrain |
P45689
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [North Caucasian Federal District, hasMountainousTerrain, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMountainousTerrain Context triple: [North Caucasian Federal District, hasMountainousTerrain, yes]
-
A.
hasMountain
Indicates that a location or region possesses or contains at least one mountain.
-
B.
hasMajorMountainRange
Indicates that one entity possesses, contains, or is geographically associated with a principal or significant mountain range.
-
C.
hasMountainRange
Indicates that one entity possesses, contains, or is geographically associated with a specific mountain range.
-
D.
hasMountainScenery
Indicates that a place or area features views or landscapes dominated by mountains.
-
E.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6a1280c8190b59a2afd30312c02 |
completed | March 8, 2026, 4:41 p.m. |
| PD | Predicate disambiguation | batch_69ad9e02677c8190a21d93b1259b2761 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f7c21c819087e9992f5fe30a37 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:06 p.m.