Triple
T27679478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whiskey Ring scandal |
E697868
|
entity |
| Predicate | amountRecovered |
P37390
|
FINISHED |
| Object | over $3,000,000 in unpaid taxes and fines |
—
|
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: over $3,000,000 in unpaid taxes and fines | Statement: [Whiskey Ring scandal, amountRecovered, over $3,000,000 in unpaid taxes and fines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: amountRecovered Context triple: [Whiskey Ring scandal, amountRecovered, over $3,000,000 in unpaid taxes and fines]
-
A.
amountInvolvedApprox
Indicates that the relationship specifies an approximate value or quantity involved in an action, event, or transaction.
-
B.
recoveredIn
chosen
Indicates that something lost, damaged, or impaired has been restored or regained within a particular context, process, or location.
-
C.
recoveredThrough
Indicates that something was regained, restored, or obtained again by means of a specified method, process, or intermediary.
-
D.
receivedSettlementAmount
Indicates that an entity has obtained a specified amount of money or value as part of a settlement.
-
E.
approximateValueStolenInUSDAtTheTime
Indicates the estimated amount of money, in U.S. dollars and valued at the time of the theft, that was stolen in the described incident.
- 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_69ef590d458c81909583290c3cd0478b |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6353654188190915266b42fb1885a |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f62c1a92648190835a2c5250d8c758 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:45 p.m.