Triple

T652940
Position Surface form Disambiguated ID Type / Status
Subject German Foreign Office E11382 entity
Predicate hasAbbreviation P43 FINISHED
Object AA E41364 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: AA | Statement: [German Foreign Office, hasAbbreviation, AA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AA
Context triple: [German Foreign Office, hasAbbreviation, AA]
  • A. AA chosen
    AA was the common abbreviation for the German Foreign Office (Auswärtiges Amt) during the Nazi era.
  • B. AA
    AA is the two-letter IATA airline designator used to identify American Airlines in flight schedules, tickets, and aviation systems.
  • C. AAA
    AAA was a New Deal-era U.S. government agency created to regulate agricultural production and stabilize farm prices during the Great Depression.
  • D. AAR
    AAR is the American Association of Railroads' wheel arrangement classification system commonly used to describe locomotive axle configurations in North America.
  • E. AAC
    AAC is a leading peer-reviewed scientific journal that publishes research on antimicrobial agents, chemotherapy, and related aspects of infectious diseases.
  • 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f4a660c8190b887cb4da01ef7ae completed March 1, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69a591486b708190b0191e958c6c8851 completed March 2, 2026, 1:31 p.m.
Created at: March 1, 2026, 7:36 p.m.