Triple
T6904789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Executive Order 6102 |
E159784
|
entity |
| Predicate | compensationRate |
P74030
|
FINISHED |
| Object | 35 US dollars per troy ounce of fine gold |
—
|
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: 35 US dollars per troy ounce of fine gold | Statement: [Executive Order 6102, compensationRate, 35 US dollars per troy ounce of fine gold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compensationRate Context triple: [Executive Order 6102, compensationRate, 35 US dollars per troy ounce of fine gold]
-
A.
compensationCategory
Indicates the type or classification of compensation associated with an entity, such as how or in what form payment or remuneration is provided.
-
B.
compensationModel
Indicates the type or structure of payment or rewards provided in exchange for work, services, or performance.
-
C.
compensationPolicy
Indicates the rules or guidelines that govern how compensation (such as salary, bonuses, or benefits) is determined and provided.
-
D.
compensated
Indicates that one entity provides payment or some form of recompense to another entity in return for goods, services, or loss incurred.
-
E.
rate
Indicates the numerical evaluation or assessment assigned by one entity to another based on perceived quality, performance, or value.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d989c13081908a2e346cde9e3a50 |
completed | March 27, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b7681481909ec50509b19fcf81 |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8c48ba48190b8d3aa7b8d22816b |
completed | March 27, 2026, 7:21 p.m. |
Created at: March 27, 2026, 2:25 p.m.