Triple
T8693654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urbanized Area Formula Program |
E206351
|
entity |
| Predicate | allocationFactor |
P36238
|
FINISHED |
| Object | population |
—
|
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: population | Statement: [Urbanized Area Formula Program, allocationFactor, population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allocationFactor Context triple: [Urbanized Area Formula Program, allocationFactor, population]
-
A.
allocation
Indicates the distribution or assignment of resources, responsibilities, or items among entities according to some rule or plan.
-
B.
allocationShare
chosen
Indicates the proportion or portion of a total resource, amount, or benefit that is assigned to a particular entity within an allocation.
-
C.
allocationType
Indicates the specific manner or category by which resources, responsibilities, or items are assigned or distributed among entities.
-
D.
rollOffFactor
Indicates how quickly the influence or intensity of something decreases as distance or another parameter increases.
-
E.
allocatesAccordingTo
Indicates that one entity distributes or assigns resources, tasks, or responsibilities to others based on a specified rule, criterion, or plan.
- 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_69ca835481fc819084e33d3bc883bfa6 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5826bbb48190a212fb1bb06e05e6 |
completed | March 31, 2026, 11:26 p.m. |
| PD | Predicate disambiguation | batch_69cc4569f9048190b9c86b4c81103d35 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:33 p.m.