Triple

T1998810
Position Surface form Disambiguated ID Type / Status
Subject European Union–United States relations E43417 entity
Predicate hasKeyFramework P9140 FINISHED
Object EU–US Data Privacy Framework
The EU–US Data Privacy Framework is a transatlantic data-transfer agreement that sets rules and safeguards for protecting the personal data of EU citizens when it is transferred to and processed in the United States.
E221480 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: EU–US Data Privacy Framework | Statement: [European Union–United States relations, hasKeyFramework, EU–US Data Privacy Framework]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EU–US Data Privacy Framework
Context triple: [European Union–United States relations, hasKeyFramework, EU–US Data Privacy Framework]
  • A. New York State Department of Financial Services Cybersecurity Regulation
    The New York State Department of Financial Services Cybersecurity Regulation is a pioneering set of cybersecurity requirements for financial institutions operating in New York, mandating robust risk-based programs, incident reporting, and governance to protect consumers and the financial system from cyber threats.
  • B. GDPR
    The GDPR (General Data Protection Regulation) is a comprehensive European Union data protection law that governs how organizations collect, process, and store personal data of individuals in the EU.
  • C. Joint Committee on Personal Data Protection Bill
    The Joint Committee on Personal Data Protection Bill was a parliamentary panel in India tasked with examining and recommending changes to the country’s proposed comprehensive data protection legislation.
  • D. European Data Protection Supervisor
    The European Data Protection Supervisor is the independent EU authority responsible for overseeing the protection of personal data and privacy within European Union institutions and bodies.
  • E. Cybersecurity Information Sharing Act of 2015
    The Cybersecurity Information Sharing Act of 2015 is a U.S. federal law that facilitates the sharing of cyber threat information between private companies and the government to improve national cybersecurity while addressing privacy and civil liberties concerns.
  • 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: EU–US Data Privacy Framework
Triple: [European Union–United States relations, hasKeyFramework, EU–US Data Privacy Framework]
Generated description
The EU–US Data Privacy Framework is a transatlantic data-transfer agreement that sets rules and safeguards for protecting the personal data of EU citizens when it is transferred to and processed in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: EU–US Data Privacy Framework
Target entity description: The EU–US Data Privacy Framework is a transatlantic data-transfer agreement that sets rules and safeguards for protecting the personal data of EU citizens when it is transferred to and processed in the United States.
  • A. New York State Department of Financial Services Cybersecurity Regulation
    The New York State Department of Financial Services Cybersecurity Regulation is a pioneering set of cybersecurity requirements for financial institutions operating in New York, mandating robust risk-based programs, incident reporting, and governance to protect consumers and the financial system from cyber threats.
  • B. GDPR
    The GDPR (General Data Protection Regulation) is a comprehensive European Union data protection law that governs how organizations collect, process, and store personal data of individuals in the EU.
  • C. Joint Committee on Personal Data Protection Bill
    The Joint Committee on Personal Data Protection Bill was a parliamentary panel in India tasked with examining and recommending changes to the country’s proposed comprehensive data protection legislation.
  • D. European Data Protection Supervisor
    The European Data Protection Supervisor is the independent EU authority responsible for overseeing the protection of personal data and privacy within European Union institutions and bodies.
  • E. Cybersecurity Information Sharing Act of 2015
    The Cybersecurity Information Sharing Act of 2015 is a U.S. federal law that facilitates the sharing of cyber threat information between private companies and the government to improve national cybersecurity while addressing privacy and civil liberties concerns.
  • 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_69a88715dbbc8190b2299e29e955d997 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb87dc8d08190907a6579c2b26d01 completed March 7, 2026, 5:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae034122ec819096a72685b34c84b9 completed March 8, 2026, 11:16 p.m.
NEDg Description generation batch_69ae03b52ed08190a8c8fb8f81073bb3 completed March 8, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_69ae0433b90c81909af348d9a3dcdbec completed March 8, 2026, 11:20 p.m.
Created at: March 4, 2026, 7:37 p.m.