Triple
T6557528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Remus |
E152486
|
entity |
| Predicate | wealth |
P8003
|
FINISHED |
| Object | became a multimillionaire from bootlegging |
—
|
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: became a multimillionaire from bootlegging | Statement: [George Remus, wealth, became a multimillionaire from bootlegging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wealth Context triple: [George Remus, wealth, became a multimillionaire from bootlegging]
-
A.
richIn
Indicates that something contains a high amount or concentration of a particular substance, quality, or resource.
-
B.
wealthSource
chosen
Indicates the relationship by which an entity obtains or derives its wealth from a particular source.
-
C.
inheritsWealth
Indicates that one entity receives wealth or assets passed down from another, typically after the latter’s death.
-
D.
capital
Indicates that one place serves as the official seat of government or primary administrative center for another political entity.
-
E.
viewOnWealth
Indicates a person’s attitude, belief, or perspective regarding wealth and its importance or use.
- 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_69c688058d6881908c19b309cc55dbfa |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6c1b15d3481908ae66e3d7564b352 |
completed | March 27, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c6acf6d4148190914b19e9affd8c76 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:52 p.m.