Triple
T36000902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarekjiegná |
E1041126
|
entity |
| Predicate | humanSettlementProximity |
P103841
|
FINISHED |
| Object | far from major 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: far from major settlements | Statement: [Sarekjiegná, humanSettlementProximity, far from major settlements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: humanSettlementProximity Context triple: [Sarekjiegná, humanSettlementProximity, far from major settlements]
-
A.
nearbySettlements
Indicates that one settlement is located close to another settlement in geographic space.
-
B.
hasNearbySettlementDensity
Indicates that an entity is associated with a concentration of settlements located within a nearby surrounding area.
-
C.
nearbySettlementRegion
Indicates that a settlement is located close to or within the surrounding area of a specified region.
-
D.
nearbySettlementStatus
chosen
Indicates whether a settlement is located close enough to another reference point or area to be considered nearby.
-
E.
hasNearestLargerSettlement
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
- 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_69f76e2a02208190aedd1f9025a8b300 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.