Triple
T731514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacKenzie Scott |
E14839
|
entity |
| Predicate | hasDonatedAmountApproximate |
P499
|
FINISHED |
| Object | tens of billions of US dollars |
—
|
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: tens of billions of US dollars | Statement: [MacKenzie Scott, hasDonatedAmountApproximate, tens of billions of US dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDonatedAmountApproximate Context triple: [MacKenzie Scott, hasDonatedAmountApproximate, tens of billions of US dollars]
-
A.
donated
chosen
Indicates that one entity voluntarily gave something of value (such as money, goods, or time) to another entity, typically without expecting anything in return.
-
B.
hasMonetaryGrant
Indicates that an entity provides or receives a monetary grant from another entity.
-
C.
donationYear
Indicates the specific calendar year in which a donation or gift was made.
-
D.
monetaryValueSponsor
Indicates that a sponsor provides or assigns a specific monetary value (amount of funding) to another entity or activity.
-
E.
tributeMethod
Indicates the means or manner by which tribute is given, delivered, or fulfilled between parties.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f9b7608190bf97c8418a26e632 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.