Triple
T4018775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacKenzie Scott |
E91227
|
entity |
| Predicate | donationStyle |
P53474
|
FINISHED |
| Object | unrestricted grants |
—
|
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: unrestricted grants | Statement: [MacKenzie Scott, donationStyle, unrestricted grants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: donationStyle Context triple: [MacKenzie Scott, donationStyle, unrestricted grants]
-
A.
tributeMethod
Indicates the means or manner by which tribute is given, delivered, or fulfilled between parties.
-
B.
donated
Indicates that one entity voluntarily gave something of value (such as money, goods, or time) to another entity, typically without expecting anything in return.
-
C.
tributeSystem
Indicates a relationship where one entity regularly provides payments, goods, or services to another as a sign of submission, allegiance, or obligation.
-
D.
donatedToState
Indicates that an entity has given or transferred something, such as money, goods, or assets, as a donation to a state or state-level governmental body.
-
E.
dedicationType
Indicates the specific kind or category of dedication that characterizes the relationship or action between entities.
- F. None of above. chosen
Provenance (4 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_69aed9618b04819081750d979d2af098 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaa984948190a252eaeb9dbae454 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8fc78ec819092d4dab88d85a141 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa815f2c8190818c9ffd9d1bf478 |
completed | March 9, 2026, 4:51 p.m. |
Created at: March 9, 2026, 3:35 p.m.