Triple
T8391540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Money Laundering and Financial Crimes Strategy Act of 1998 |
E197953
|
entity |
| Predicate | enforcementTarget |
P43080
|
FINISHED |
| Object | money laundering schemes |
—
|
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: money laundering schemes | Statement: [Money Laundering and Financial Crimes Strategy Act of 1998, enforcementTarget, money laundering schemes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enforcementTarget Context triple: [Money Laundering and Financial Crimes Strategy Act of 1998, enforcementTarget, money laundering schemes]
-
A.
lawEnforcementTarget
chosen
Indicates that an entity is the focus or object of attention, investigation, or action by law enforcement authorities.
-
B.
enforcement
Indicates the act of compelling compliance with rules, laws, or agreements through monitoring, pressure, or sanctions.
-
C.
enforcementModel
Indicates the method or framework by which rules, policies, or constraints are applied, monitored, and enforced within a system or interaction.
-
D.
enforcementStrength
Indicates the degree or intensity with which rules, laws, or policies are applied and enforced in a given context.
-
E.
enforcedOn
Indicates that a rule, policy, or constraint is applied with authority to a particular target or subject.
- 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_69ca82f749388190bffbea6dfb509016 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb810e16b081908e2c25bfb9d590ed |
completed | March 31, 2026, 8:08 a.m. |
| PD | Predicate disambiguation | batch_69cb70d24b248190a326aa6804f942b5 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:03 p.m.