Triple
T7492770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uyui District |
E177045
|
entity |
| Predicate | hasRuralPopulationMajority |
P47416
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Uyui District, hasRuralPopulationMajority, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuralPopulationMajority Context triple: [Uyui District, hasRuralPopulationMajority, true]
-
A.
isPredominantlyRural
chosen
Indicates that a place or region is characterized mainly by rural features, such as low population density and extensive non-urban land use.
-
B.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
-
C.
hasRuralAreaShare
Indicates the proportion of an entity’s total area or population that is classified as rural.
-
D.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
-
E.
isRuralCounty
Indicates that a given county is classified as rural rather than urban based on demographic, geographic, or administrative criteria.
- 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_69c69f2583808190bd1a4936c42a5815 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81b431481908214b69c6c8d83bc |
completed | March 27, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d266d88190982cf5d2ee2e9564 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:43 p.m.