Triple

T20082187
Position Surface form Disambiguated ID Type / Status
Subject British forces in Georgia E500028 entity
Predicate garrisonedIn P2911 FINISHED
Object Augusta, Georgia NE NERFINISHED

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: Augusta, Georgia | Statement: [British forces in Georgia, garrisonedIn, Augusta, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Augusta, Georgia
Context triple: [British forces in Georgia, garrisonedIn, Augusta, Georgia]
  • A. Augusta, Georgia
    Augusta, Georgia is a major city in eastern Georgia known for hosting the Masters Tournament in professional golf and for its historic and military significance.
  • B. Augusta
    Augusta was an honorific title used for empresses and other high-ranking women in the Roman and Byzantine Empires, signifying imperial dignity and status.
  • C. Augusta chosen
    Augusta is a major city in eastern Georgia, United States, best known for hosting the annual Masters Tournament in professional golf.
  • D. Augusta
    Augusta is a coastal town and important industrial and port center in southeastern Sicily, Italy.
  • E. Augusta
    Augusta is a noblewoman historically recognized as the daughter of Galla.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e665588a9c8190886b693b13a215a8 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.