Triple
T11719699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuser family |
E278593
|
entity |
| Predicate | engagedInPhilanthropyField |
P9241
|
FINISHED |
| Object | conservation |
—
|
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: conservation | Statement: [Kuser family, engagedInPhilanthropyField, conservation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: engagedInPhilanthropyField Context triple: [Kuser family, engagedInPhilanthropyField, conservation]
-
A.
fieldOfPhilanthropy
chosen
Indicates that an entity is engaged in or associated with a particular area or domain of philanthropic activity.
-
B.
hasPhilanthropicRole
Indicates that an entity holds or performs a role related to charitable, philanthropic, or socially beneficial activities.
-
C.
genreOfPhilanthropy
Indicates the specific type or category of philanthropic activity to which an act, initiative, or organization belongs.
-
D.
regionOfPhilanthropy
Indicates the geographic area or location where philanthropic activities, donations, or charitable efforts are directed or take place.
-
E.
partnerInPhilanthropy
Indicates a relationship where two or more entities collaborate as partners in philanthropic activities, initiatives, or charitable efforts.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4c26e4c8190ae30d906b4fd4221 |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7d483081909c2a101087515d74 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.