Triple
T230493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mitchell Kapor |
E4399
|
entity |
| Predicate | typeOfPhilanthropy |
P3801
|
FINISHED |
| Object | technology 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: technology education | Statement: [Mitchell Kapor, typeOfPhilanthropy, technology education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfPhilanthropy Context triple: [Mitchell Kapor, typeOfPhilanthropy, technology education]
-
A.
genreOfPhilanthropy
chosen
Indicates the specific type or category of philanthropic activity to which an act, initiative, or organization belongs.
-
B.
partnerInPhilanthropy
Indicates a relationship where two or more entities collaborate as partners in philanthropic activities, initiatives, or charitable efforts.
-
C.
hasCharitableFoundation
Indicates that an entity maintains or is associated with a charitable foundation, typically for philanthropic or nonprofit activities.
-
D.
nonprofitStatus
Indicates that an entity operates as a nonprofit organization, typically meeting legal or regulatory criteria for nonprofit status.
-
E.
sponsoringOrganizationType
Indicates the kind or category of organization that provides sponsorship or support in the described relationship or 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25e0868708190ad551ca06cc57f4a |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b5a075081909b0e9b88c1492d5a |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.