Triple

T20276326
Position Surface form Disambiguated ID Type / Status
Subject GA-02 E503025 entity
Predicate hasCity P316 FINISHED
Object Attapulgus, Georgia E359211 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: Attapulgus, Georgia | Statement: [GA-02, hasCity, Attapulgus, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Attapulgus, Georgia
Context triple: [GA-02, hasCity, Attapulgus, Georgia]
  • A. Attapulgus, Georgia chosen
    Attapulgus, Georgia is a small rural city in southwestern Georgia known historically for its clay mining and agricultural surroundings.
  • B. Alapaha, Georgia
    Alapaha, Georgia is a small rural town in Berrien County known for its historic Southern character and proximity to the Alapaha River in south-central Georgia.
  • C. Tallapoosa, Georgia
    Tallapoosa, Georgia is a small city in Haralson County in western Georgia, known for its historic downtown and location near the Alabama state line.
  • D. Sylvania, Georgia
    Sylvania, Georgia is a small city in Screven County known as the county seat and a historic community in eastern Georgia.
  • E. De Soto, Georgia
    De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e675e3df68819096fb859bc92a0da1 completed April 20, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08939c764081909c87a17a5973b5b4 completed May 16, 2026, 3:56 p.m.
Created at: April 16, 2026, 10:32 a.m.