Triple

T8391538
Position Surface form Disambiguated ID Type / Status
Subject Money Laundering and Financial Crimes Strategy Act of 1998 E197953 entity
Predicate relatedTo P37 FINISHED
Object United States anti–money laundering regulations
United States anti–money laundering regulations are a framework of federal laws, rules, and enforcement measures designed to detect, prevent, and prosecute the concealment of illicit funds within the U.S. financial system.
E730863 NE FINISHED

How this triple was built (4 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: United States anti–money laundering regulations | Statement: [Money Laundering and Financial Crimes Strategy Act of 1998, relatedTo, United States anti–money laundering regulations]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: United States anti–money laundering regulations
Context triple: [Money Laundering and Financial Crimes Strategy Act of 1998, relatedTo, United States anti–money laundering regulations]
  • A. Annunzio-Wylie Anti-Money Laundering Act
    The Annunzio-Wylie Anti-Money Laundering Act is a 1992 U.S. federal law that strengthened anti-money laundering controls, expanded reporting requirements, and enhanced enforcement powers against financial crimes.
  • B. European Union anti-money laundering directives
    The European Union anti-money laundering directives are a series of EU-wide legal measures that require member states to prevent, detect, and prosecute money laundering and terrorist financing through harmonized rules for financial institutions and other obliged entities.
  • C. Money Laundering Suppression Act of 1994
    The Money Laundering Suppression Act of 1994 is a U.S. federal law that strengthened anti–money laundering regulations, particularly by enhancing reporting, oversight, and enforcement mechanisms for financial institutions.
  • D. Money Laundering and Financial Crimes Strategy Act of 1998
    The Money Laundering and Financial Crimes Strategy Act of 1998 is a U.S. federal law that strengthened the nation’s anti–money laundering framework by enhancing coordination, enforcement, and strategic planning among financial regulators and law enforcement agencies.
  • E. Bank Secrecy Act
    The Bank Secrecy Act is a U.S. law that requires financial institutions to assist government agencies in detecting and preventing money laundering, terrorist financing, and other financial crimes.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: United States anti–money laundering regulations
Triple: [Money Laundering and Financial Crimes Strategy Act of 1998, relatedTo, United States anti–money laundering regulations]
Generated description
United States anti–money laundering regulations are a framework of federal laws, rules, and enforcement measures designed to detect, prevent, and prosecute the concealment of illicit funds within the U.S. financial system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: United States anti–money laundering regulations
Target entity description: United States anti–money laundering regulations are a framework of federal laws, rules, and enforcement measures designed to detect, prevent, and prosecute the concealment of illicit funds within the U.S. financial system.
  • A. Annunzio-Wylie Anti-Money Laundering Act
    The Annunzio-Wylie Anti-Money Laundering Act is a 1992 U.S. federal law that strengthened anti-money laundering controls, expanded reporting requirements, and enhanced enforcement powers against financial crimes.
  • B. European Union anti-money laundering directives
    The European Union anti-money laundering directives are a series of EU-wide legal measures that require member states to prevent, detect, and prosecute money laundering and terrorist financing through harmonized rules for financial institutions and other obliged entities.
  • C. Money Laundering Suppression Act of 1994
    The Money Laundering Suppression Act of 1994 is a U.S. federal law that strengthened anti–money laundering regulations, particularly by enhancing reporting, oversight, and enforcement mechanisms for financial institutions.
  • D. Money Laundering and Financial Crimes Strategy Act of 1998
    The Money Laundering and Financial Crimes Strategy Act of 1998 is a U.S. federal law that strengthened the nation’s anti–money laundering framework by enhancing coordination, enforcement, and strategic planning among financial regulators and law enforcement agencies.
  • E. Bank Secrecy Act
    The Bank Secrecy Act is a U.S. law that requires financial institutions to assist government agencies in detecting and preventing money laundering, terrorist financing, and other financial crimes.
  • F. None of above. chosen

Provenance (5 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.
NED1 Entity disambiguation (via context triple) batch_69cde84d6f3c8190ba12905ba5900087 completed April 2, 2026, 3:53 a.m.
NEDg Description generation batch_69cdebfc63e8819087f5c1d588b58e21 completed April 2, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_69cded77618c81909e8786ccd2f3e4b6 completed April 2, 2026, 4:15 a.m.
Created at: March 30, 2026, 6:03 p.m.