Triple
T4437992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrogate |
E95697
|
entity |
| Predicate | earningsUSD |
P52574
|
FINISHED |
| Object | 17000000+ |
—
|
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: 17000000+ | Statement: [Arrogate, earningsUSD, 17000000+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earningsUSD Context triple: [Arrogate, earningsUSD, 17000000+]
-
A.
valueInUSD
chosen
Indicates that a given amount or asset is expressed or evaluated in terms of its monetary value in United States dollars (USD).
-
B.
netIncome
Indicates the financial result of an entity’s operations over a period, calculated as total revenues minus all expenses, taxes, and other deductions.
-
C.
profitsFrom
Indicates that one entity gains financial or material benefit as a result of another entity’s actions, existence, or situation.
-
D.
mileEarningUnit
Indicates the unit or basis (e.g., per mile, per dollar) used to calculate or award mileage or points in a mileage-earning relationship.
-
E.
currency
Indicates that one entity serves as the medium of exchange or monetary unit used by another entity (such as a country, region, or system).
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3558c75948190875a5fb10eac0597 |
completed | March 13, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69b34f6078cc8190831b89f404198cc5 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:31 p.m.