Triple

T4132785
Position Surface form Disambiguated ID Type / Status
Subject AEF E85078 entity
Predicate shortName P43 FINISHED
Object AEF E85078 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: AEF | Statement: [AEF, shortName, AEF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AEF
Context triple: [AEF, shortName, AEF]
  • A. AEF chosen
    AEF was the common abbreviation for French Equatorial Africa, a former federation of French colonial territories in central Africa.
  • B. EAF
    The EAF is the aerial warfare branch of Egypt's armed forces, responsible for defending the country's airspace and conducting air operations.
  • C. EOAF
    EOAF is the abbreviated name for the Massachusetts Executive Office for Administration and Finance, the state agency responsible for overseeing the Commonwealth’s budget, financial management, and administrative policy.
  • D. BEF
    The BEF was the British Army force deployed to France at the start of World War II, which fought in the early campaigns and was famously evacuated from Dunkirk in 1940.
  • E. AFT
    AFT is a major American labor union representing teachers and other education professionals across the United States.
  • 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_69aed935ccd881909dc61f81bcdb7a78 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af022f55fc81909f2a1a04d0ea59e6 completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576c4c0888190be156d093ea11207 completed March 14, 2026, 2:55 p.m.
Created at: March 9, 2026, 3:42 p.m.