Triple
T25028330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Executive Order 6260 |
E626769
|
entity |
| Predicate | penaltyMaximumFineUSD |
P28687
|
FINISHED |
| Object | 10000 |
—
|
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: 10000 | Statement: [Executive Order 6260, penaltyMaximumFineUSD, 10000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: penaltyMaximumFineUSD Context triple: [Executive Order 6260, penaltyMaximumFineUSD, 10000]
-
A.
maximumPenaltyForIndividuals
Indicates the highest allowable penalty that can be imposed on individual persons under a given rule, law, or policy.
-
B.
statutoryLimitPerIncidentUSD
chosen
Indicates the maximum monetary amount, in U.S. dollars, that is legally allowed to be claimed or paid for a single incident under a specific statute or regulation.
-
C.
maximumPenaltyForOrganisations
Indicates the highest level of penalty that can be imposed on organisations under a given rule or legal framework.
-
D.
penaltyMagnitude
Indicates the size or severity of a penalty imposed in a given situation or relationship.
-
E.
punitiveDamagesAwarded
Indicates that a court has granted punitive damages against a party, typically to punish wrongful conduct and deter similar future behavior.
- 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_69e2ff28ee3881909c626af002457a4a |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44f6c0538819084ae65fed91c4c86 |
completed | May 1, 2026, 6:59 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 6:07 a.m.