Triple
T2996126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAF Honington |
E81069
|
entity |
| Predicate | hasPerimeter |
P6131
|
FINISHED |
| Object | fenced military area |
—
|
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: fenced military area | Statement: [RAF Honington, hasPerimeter, fenced military area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPerimeter Context triple: [RAF Honington, hasPerimeter, fenced military area]
-
A.
perimeter
Indicates the total length around the boundary of a two-dimensional shape or region.
-
B.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
C.
hasGeometry
Indicates that an entity is associated with a specific geometric representation or spatial form.
-
D.
enclosesArea
Indicates that one entity surrounds and contains a bounded region of space occupied or defined by another.
-
E.
hasBoundaryFeature
chosen
Indicates that a boundary (such as an edge, border, or limit) of one entity is characterized, marked, or defined by a specific feature or element.
- 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99f481688190ae8cd1e057f9dfc7 |
completed | March 8, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69ad9615fefc8190ad96da92519cb7a3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.