Triple
T11700711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St John Ambulance |
E278116
|
entity |
| Predicate | usesWorkforceType |
P11922
|
FINISHED |
| Object | volunteers |
—
|
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: volunteers | Statement: [St John Ambulance, usesWorkforceType, volunteers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesWorkforceType Context triple: [St John Ambulance, usesWorkforceType, volunteers]
-
A.
hasWorkforceType
chosen
Indicates the type or category of workforce associated with an entity (such as permanent, temporary, contract, or part-time).
-
B.
associatedWithWorkforce
Indicates a relationship in which an entity is connected or related to a particular workforce, such as its members, activities, or management.
-
C.
employedSystem
Indicates that a system is used or operated in the context of an employment or work-related arrangement.
-
D.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
E.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49a025881909377c81d3debf465 |
completed | April 10, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69d88a7b30948190b616a9db5c5488d5 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.