Triple
T36897085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAE West Freugh |
E911918
|
entity |
| Predicate | hasTestingArea |
P186658
|
FINISHED |
| Object | Luce Bay firing range |
—
|
NE NERFINISHED |
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: Luce Bay firing range | Statement: [RAE West Freugh, hasTestingArea, Luce Bay firing range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTestingArea Context triple: [RAE West Freugh, hasTestingArea, Luce Bay firing range]
-
A.
testArea
chosen
Indicates that an entity is designated as a test-specific area or region used for experiments, trials, or validation activities.
-
B.
hasAreaOfCoverage
Indicates that an entity provides services, influence, or applicability within a specified geographic or conceptual region.
-
C.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
hasAreaNumber
Indicates that an entity is associated with a specific area identified by a numerical code.
-
E.
hasExampleArea
Indicates that something includes or is associated with a specific area used as an example or illustrative region.
- 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_69f76e841b54819097e7fa768bbc70b2 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe9dfaa2d08190b2084f63f842eb6b |
completed | May 9, 2026, 2:37 a.m. |
| PD | Predicate disambiguation | batch_69fe9bba947c81908b0b2b92a4d19b37 |
completed | May 9, 2026, 2:28 a.m. |
Created at: May 3, 2026, 4:13 p.m.