Triple

T15657910
Position Surface form Disambiguated ID Type / Status
Subject Metro Atlanta Southside E376492 entity
Predicate hasPart P35 FINISHED
Object Lovejoy, Georgia E69963 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: Lovejoy, Georgia | Statement: [Metro Atlanta Southside, hasPart, Lovejoy, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lovejoy, Georgia
Context triple: [Metro Atlanta Southside, hasPart, Lovejoy, Georgia]
  • A. Lovejoy, Georgia chosen
    Lovejoy, Georgia is a small city in the southern Atlanta metropolitan area known for its Civil War history and suburban residential character.
  • B. Lovett, Georgia
    Lovett, Georgia is a small unincorporated rural community located in Laurens County in the central part of the state.
  • C. Whigham, Georgia
    Whigham, Georgia is a small rural city in the southwestern part of the state known for its tight-knit community and agricultural surroundings.
  • D. Richwood, Georgia
    Richwood, Georgia is a small unincorporated rural community located in Dooly County in the U.S. state of Georgia.
  • E. Leary, Georgia
    Leary, Georgia is a small rural city located in southwestern Georgia within Calhoun County.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ef3cb8c8190a10815b675b341c1 completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe4670e8881908bc9f3879ba208ba completed May 10, 2026, 1:50 a.m.
Created at: April 10, 2026, 4:15 a.m.