Triple
T11506860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battagram District |
E272806
|
entity |
| Predicate | populationRuralUrbanDistribution |
P40698
|
FINISHED |
| Object | largely rural |
—
|
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: largely rural | Statement: [Battagram District, populationRuralUrbanDistribution, largely rural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRuralUrbanDistribution Context triple: [Battagram District, populationRuralUrbanDistribution, largely rural]
-
A.
urbanRuralSplit
chosen
Indicates a division or distinction between urban and rural areas, conditions, or populations.
-
B.
isRuralOrUrban
Indicates whether an entity is classified as being in a rural area or an urban area.
-
C.
statusInUrbanAreas
Indicates the condition, prevalence, or situation of something specifically within urban areas.
-
D.
populationConcentration
Indicates the degree to which a population is densely gathered or distributed within a specific area or region.
-
E.
urbanizationLevel
Indicates the degree to which an area or population is characterized by urban development, infrastructure, and density of human settlement.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d86db43a648190be859bec2fe9f43b |
completed | April 10, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.