Triple
T27320315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Zucker |
E689473
|
entity |
| Predicate | hasPhilanthropicArea |
P9241
|
FINISHED |
| Object | medical education |
—
|
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: medical education | Statement: [Donald Zucker, hasPhilanthropicArea, medical education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhilanthropicArea Context triple: [Donald Zucker, hasPhilanthropicArea, medical education]
-
A.
hasPhilanthropicRole
Indicates that an entity holds or performs a role related to charitable, philanthropic, or socially beneficial activities.
-
B.
hasPhilanthropicProgram
Indicates that an entity operates or participates in an organized initiative aimed at providing charitable or philanthropic support.
-
C.
associatedWithPhilanthropyIn
Indicates a relationship where an entity is involved in or connected to philanthropic activities within a specific place or context.
-
D.
regionOfPhilanthropy
Indicates the geographic area or location where philanthropic activities, donations, or charitable efforts are directed or take place.
-
E.
fieldOfPhilanthropy
chosen
Indicates that an entity is engaged in or associated with a particular area or domain of philanthropic activity.
- 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_69ef355c53a08190a8a92e355a7ce115 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 27, 2026, 11:32 a.m.