Triple
T7339615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medical Reserve Corps |
E169213
|
entity |
| Predicate | volunteersSupport |
P16415
|
FINISHED |
| Object | local public health authorities |
—
|
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: local public health authorities | Statement: [Medical Reserve Corps, volunteersSupport, local public health authorities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: volunteersSupport Context triple: [Medical Reserve Corps, volunteersSupport, local public health authorities]
-
A.
volunteeredFor
Indicates that an entity willingly offered their time or services to support or participate in an activity, cause, or organization.
-
B.
receivedVolunteersFrom
Indicates that one entity accepted or was provided with volunteers originating from another entity.
-
C.
providesSupportTo
chosen
Indicates that one entity offers help, resources, or reinforcement to another entity to aid its function, stability, or success.
-
D.
typeOfVolunteerUnit
Indicates that one entity is a specific kind or category of volunteer unit in relation to another entity.
-
E.
civilSocietySupportedBy
Indicates that a civil society organization receives backing, assistance, or resources from a specified supporter or source.
- 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_69c68a57710481909f0c1f3c6ebdb6f2 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:04 p.m.