Triple

T16738763
Position Surface form Disambiguated ID Type / Status
Subject Trump v. Deutsche Bank AG E406784 entity
Predicate hasParty P1790 FINISHED
Object Deutsche Bank AG E373967 NE 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: Deutsche Bank AG | Statement: [Trump v. Deutsche Bank AG, hasParty, Deutsche Bank AG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deutsche Bank AG
Context triple: [Trump v. Deutsche Bank AG, hasParty, Deutsche Bank AG]
  • A. Deutsche Bank chosen
    Deutsche Bank is a major global investment bank and financial services company headquartered in Frankfurt, Germany.
  • B. Commerzbank AG
    Commerzbank AG is a major German commercial bank headquartered in Frankfurt, known as one of the country’s leading financial institutions serving corporate, institutional, and retail clients.
  • C. Dresdner Bank
    Dresdner Bank was one of Germany’s major commercial banks, historically influential in the country’s financial and industrial development.
  • D. Deutsche Rentenbank
    Deutsche Rentenbank was the German financial institution established in 1923 to stabilize the currency and restore confidence during the hyperinflation crisis of the Weimar Republic.
  • E. ABN AMRO
    ABN AMRO is a major Dutch bank headquartered in Amsterdam, known for providing a wide range of retail, private, and corporate banking services internationally.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e39c3c808c8190b3300edeb7c7bca9 completed April 18, 2026, 2:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d50df9c81909452f330eb4336e4 completed May 10, 2026, 2:59 p.m.
Created at: April 10, 2026, 5:20 a.m.