Triple

T14610204
Position Surface form Disambiguated ID Type / Status
Subject served by Interstate 75 E342938 entity
Predicate appliesTo P1129 FINISHED
Object Morrow, Georgia E68444 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: Morrow, Georgia | Statement: [served by Interstate 75, appliesTo, Morrow, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Morrow, Georgia
Context triple: [served by Interstate 75, appliesTo, Morrow, Georgia]
  • A. Morrow, Georgia chosen
    Morrow, Georgia is a small suburban city in the Atlanta metropolitan area known for housing Clayton State University and various retail and commercial centers.
  • B. Montrose, Georgia
    Montrose, Georgia is a small rural community located in central Georgia within Laurens County.
  • C. Sylvania, Georgia
    Sylvania, Georgia is a small city in Screven County known as the county seat and a historic community in eastern Georgia.
  • D. Milford, Georgia
    Milford, Georgia is a small unincorporated community located in rural southwestern Georgia within Baker County.
  • E. Moultrie, Georgia
    Moultrie, Georgia is a small city known as an agricultural and commercial center in southwest Georgia, particularly noted for its farming, livestock, and historic downtown.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44f0dd48190a78662b5998a6722 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e7772508190bee1eb310aa40372 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 1:25 a.m.