Triple
T33945941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rehabilitation Department (Brockville General Hospital) |
E870289
|
entity |
| Predicate | mayIncludeStaffType |
P127311
|
FINISHED |
| Object | physiotherapist |
—
|
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: physiotherapist | Statement: [Rehabilitation Department (Brockville General Hospital), mayIncludeStaffType, physiotherapist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayIncludeStaffType Context triple: [Rehabilitation Department (Brockville General Hospital), mayIncludeStaffType, physiotherapist]
-
A.
mayIncludeDepartment
Indicates that one entity is allowed or able to contain or encompass a particular department as part of its structure or composition.
-
B.
staffIncluded
Indicates that staff members are included or provided as part of the associated entity, service, or arrangement.
-
C.
usesStaffCategory
chosen
Indicates that an entity employs or applies a particular category or classification of staff in its operations or context.
-
D.
mayIncludeUnitType
Indicates that something is allowed to contain or be associated with a particular type of unit.
-
E.
hasStaffingStatus
Indicates the current staffing condition or level associated with an entity, such as whether it is adequately, under-, or over-staffed.
- 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_69f3499b0dd48190b07b4b60babcee02 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:49 a.m.