Triple
T13582197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atkarsk |
E324446
|
entity |
| Predicate | hasNearbyRuralLocalities |
P54976
|
FINISHED |
| Object | Atkarsky District rural settlements |
—
|
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: Atkarsky District rural settlements | Statement: [Atkarsk, hasNearbyRuralLocalities, Atkarsky District rural settlements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyRuralLocalities Context triple: [Atkarsk, hasNearbyRuralLocalities, Atkarsky District rural settlements]
-
A.
hasRuralLocality
chosen
Indicates that an entity possesses, includes, or is associated with a rural locality (such as a village, hamlet, or countryside settlement) within its scope or jurisdiction.
-
B.
nearbySettlementRegion
Indicates that a settlement is located close to or within the surrounding area of a specified region.
-
C.
hasCommunesNear
Indicates that one entity has communes located in its nearby geographic vicinity.
-
D.
hasNearbyTraditionalVillage
Indicates that an entity is located close to or in the vicinity of a traditional village.
-
E.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
- F. None of above.
Provenance (3 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb031e8048190a5f2ea934308036c |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.