Triple
T14363793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wylam railway station |
E356171
|
entity |
| Predicate | hasStaffingLevel |
P63143
|
FINISHED |
| Object | unstaffed |
—
|
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: unstaffed | Statement: [Wylam railway station, hasStaffingLevel, unstaffed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStaffingLevel Context triple: [Wylam railway station, hasStaffingLevel, unstaffed]
-
A.
staffingLevel
chosen
Indicates the degree or adequacy of personnel assigned to perform a particular function, task, or operation.
-
B.
hasStaffingModel
Indicates that an entity is associated with or operates under a particular staffing model or staffing approach.
-
C.
hasStaffedHours
Indicates that specific hours or time periods are assigned during which staff are present and available.
-
D.
hasSupportStaff
Indicates that an entity is associated with one or more staff members who provide assistance or support services to it.
-
E.
hasFacilityLevel
Indicates the degree or tier of capability, service, or infrastructure that a particular facility possesses.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8fad48748190a0f34ca4d02f9a3c |
completed | April 14, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:15 a.m.