Triple

T10771650
Position Surface form Disambiguated ID Type / Status
Subject Middle Georgia Regional Airport E254093 entity
Predicate owner P347 FINISHED
Object City of Macon E335891 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: City of Macon | Statement: [Middle Georgia Regional Airport, owner, City of Macon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Macon
Context triple: [Middle Georgia Regional Airport, owner, City of Macon]
  • A. City of Macon chosen
    The City of Macon is a municipal government in Georgia responsible for providing local services, infrastructure, and administration for its residents.
  • B. Downtown Macon
    Downtown Macon is the central business and cultural district of Macon, Georgia, known for its historic architecture, museums, and vibrant arts and music scene.
  • C. Macon
    Macon is a surname of English and French origin borne by various notable individuals, including American statesman Nathaniel Macon.
  • D. Macon
    Macon is a small town located in Warren County, North Carolina, known for its rural character and proximity to Lake Gaston.
  • E. Macon, North Carolina
    Macon, North Carolina is a small town in Warren County known primarily as the namesake for the larger city of Macon, Georgia.
  • 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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d7329a281081909cdc4b971cf69207 completed April 9, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69de23798af48190874d7e12c5155913 completed April 14, 2026, 11:22 a.m.
Created at: April 8, 2026, 9:16 p.m.