Triple
T4412906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thunder Snow |
E94891
|
entity |
| Predicate | careerEarningsApprox |
P55500
|
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: [Thunder Snow, careerEarningsApprox, 17000000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerEarningsApprox Context triple: [Thunder Snow, careerEarningsApprox, 17000000]
-
A.
salary
Indicates the amount of monetary compensation an entity receives, typically on a regular basis, for work or services performed.
-
B.
peakEmployment
Indicates that an entity has reached its highest level of employment or workforce size during a specified period.
-
C.
payGrade
Indicates the level or category of compensation assigned to an entity, typically reflecting its rank, role, or seniority in a pay structure.
-
D.
incomeMeasure
Indicates a relationship where one entity serves as a measure or metric of another entity’s income.
-
E.
earnOn
Indicates that one entity gains income, profit, or returns as a result of another entity or activity.
- 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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b354e7b30c819082ee781dd202dcc4 |
completed | March 13, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69b34f5d0c54819085c08533bb58030a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff7018c81908ad8597e525c042b |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:29 p.m.