Triple

T9203809
Position Surface form Disambiguated ID Type / Status
Subject Julia Compton Moore E220917 entity
Predicate residence P75 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: [Julia Compton Moore, residence, Fort Benning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fort Benning
Context triple: [Julia Compton Moore, residence, 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_69ca83e8e9248190862cf3e41693b310 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd944e6208190adfcc7f75197387d completed April 1, 2026, 8:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c4e56208190a5b2749b81e467be completed April 4, 2026, 12:33 a.m.
Created at: March 30, 2026, 7:26 p.m.