Triple

T6793586
Position Surface form Disambiguated ID Type / Status
Subject Fort Moore E155995 entity
Predicate hasFormerName P65 FINISHED
Object Fort Benning E109971 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: Fort Benning | Statement: [Fort Moore, hasFormerName, Fort Benning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fort Benning
Context triple: [Fort Moore, hasFormerName, Fort Benning]
  • A. Fort Benning chosen
    Fort Benning was a major U.S. Army installation in Georgia, long known as a primary training center for infantry and airborne forces.
  • B. Fort Stewart
    Fort Stewart is a major U.S. Army installation in southeastern Georgia that serves as a key training and deployment base for armored and mechanized units.
  • C. Fort Gordon
    Fort Gordon is a United States Army installation near Augusta, Georgia, historically known for its signal and cyber operations training missions.
  • D. Fort Huachuca
    Fort Huachuca is a major U.S. Army installation in southeastern Arizona known for its roles in military intelligence, communications, and electronic testing.
  • E. Fort Bragg
    Fort Bragg is a major U.S. Army installation in North Carolina known as one of the world’s largest military bases and a central hub for airborne and special operations forces.
  • 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_69c6881844448190a65822d9b39d7f88 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2af6f908190809e39b73894e513 completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723cf2540819099b5bae43453aa92 completed March 28, 2026, 12:41 a.m.
Created at: March 27, 2026, 2:15 p.m.