Triple
T23425522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whyteleafe Primary School |
E560783
|
entity |
| Predicate | locatedInUrbanOrRuralArea |
P60791
|
FINISHED |
| Object | village |
—
|
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: village | Statement: [Whyteleafe Primary School, locatedInUrbanOrRuralArea, village]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInUrbanOrRuralArea Context triple: [Whyteleafe Primary School, locatedInUrbanOrRuralArea, village]
-
A.
locatedInUrbanizationType
Indicates that one entity is situated within, or belongs to, a specific type or category of urbanized area (e.g., city, suburb, metropolitan zone).
-
B.
isRuralOrUrban
chosen
Indicates whether an entity is classified as being in a rural area or an urban area.
-
C.
isInRuralAreaOf
Indicates that one entity is located within the rural area or countryside region associated with another entity.
-
D.
hasUrbanAreaApprox
Indicates an approximate measure or estimate of the size or extent of an entity’s urban area.
-
E.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
- 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_69e2454cb1108190ab21ada5411a7146 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a54951688190a3c5382971af3e41 |
completed | April 29, 2026, 6:29 a.m. |
| PD | Predicate disambiguation | batch_69f061f92da081908e7f1d0cd1e9b01c |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 5:47 p.m.