Triple
T4051930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CCPA |
E84603
|
entity |
| Predicate | civilPenalties |
P36372
|
FINISHED |
| Object | up to 2,500 USD per violation |
—
|
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: up to 2,500 USD per violation | Statement: [CCPA, civilPenalties, up to 2,500 USD per violation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: civilPenalties Context triple: [CCPA, civilPenalties, up to 2,500 USD per violation]
-
A.
legalCharge
Indicates that an authority has formally accused an entity of committing a specific legal offense or violation.
-
B.
violationConsequences
chosen
Indicates the negative outcomes, penalties, or repercussions that result from a violation of a rule, law, or agreement.
-
C.
penaltyProvision
Indicates that a rule, contract, or law includes a clause specifying a punishment or sanction for non-compliance or violation.
-
D.
legalConcept
Indicates a relationship where something is classified or treated as a concept defined and governed by law or legal theory.
-
E.
legalAct
Indicates that an entity performs, enacts, or is involved in a formal legal action, measure, or proceeding under a legal framework.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb8539148190990468c1429be9dd |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef90249e4819095e9e043bc4aa9a6 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.