Triple
T108146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anti-Money Laundering Act of 2020 |
E2182
|
entity |
| Predicate | increases |
P7907
|
FINISHED |
| Object | civil penalties for certain Bank Secrecy Act violations |
—
|
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: civil penalties for certain Bank Secrecy Act violations | Statement: [Anti-Money Laundering Act of 2020, increases, civil penalties for certain Bank Secrecy Act violations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: increases Context triple: [Anti-Money Laundering Act of 2020, increases, civil penalties for certain Bank Secrecy Act violations]
-
A.
accelerates
Indicates that one entity causes an increase in the speed or rate of change of another entity or process.
-
B.
strengthens
Indicates that one entity increases the power, effectiveness, or resilience of another.
-
C.
promotes
Indicates that one entity actively supports, advances, or encourages the growth, adoption, or success of another entity or outcome.
-
D.
encourages
Indicates actively motivating, supporting, or giving confidence to another entity to pursue an action, behavior, or state.
-
E.
above
Indicates that one entity is positioned higher than another along a vertical axis, without implying direct contact.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25a1199ac8190ac65ffaaf45b4f5b |
completed | Feb. 28, 2026, 2:59 a.m. |
| PD | Predicate disambiguation | batch_69a2563e7188819091e9a94e071991d7 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25a10d6448190bee47847d5c13b84 |
completed | Feb. 28, 2026, 2:59 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.