Triple
T639661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Privolnoye |
E16703
|
entity |
| Predicate | hasSettlementStatus |
P1068
|
FINISHED |
| Object | rural locality in Stavropol Krai |
—
|
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: rural locality in Stavropol Krai | Statement: [Privolnoye, hasSettlementStatus, rural locality in Stavropol Krai]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSettlementStatus Context triple: [Privolnoye, hasSettlementStatus, rural locality in Stavropol Krai]
-
A.
associatedWithSettlement
Indicates a relationship where an entity is linked or connected to a particular settlement, such as a town, village, or city.
-
B.
settlementType
chosen
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
-
C.
hasSettlementAtFoot
Indicates that a settlement is located at the base or lower slopes of a geographic feature such as a hill or mountain.
-
D.
hasHumanSettlement
Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
-
E.
servesSettlement
Indicates that one entity provides services or support to a particular settlement or community.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49f00260081909d1a679182e23d10 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0830008190a26ee158ed4dd1fe |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.