Triple

T14150639
Position Surface form Disambiguated ID Type / Status
Subject Newton County, Georgia E350667 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object Newton
Newton is the vehicle registration code used on license plates issued in Newton County, Georgia.
 E1082322 NE FINISHED

How this triple was built (4 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: Newton | Statement: [Newton County, Georgia, hasVehicleRegistrationCode, Newton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Newton
Context triple: [Newton County, Georgia, hasVehicleRegistrationCode, Newton]
  • A. Newton
    Newton is a suburban city in Massachusetts known for its residential neighborhoods, strong public schools, and proximity to Boston.
  • B. Newton
    Newton is a small settlement in West Lothian, Scotland, known primarily as a residential village within the Edinburgh commuter belt.
  • C. Newton
    Newton is a common English surname most famously associated with figures such as physicist Sir Isaac Newton and activist Huey P. Newton.
  • D. Newton
    Newton is a small Midwestern town that later became known as Rensselaer in Indiana, United States.
  • E. Newton
    Newton is a large, primarily residential planning area in eastern Singapore known for its food centre and proximity to the Orchard Road shopping district.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Newton
Triple: [Newton County, Georgia, hasVehicleRegistrationCode, Newton]
Generated description
Newton is the vehicle registration code used on license plates issued in Newton County, Georgia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Newton
Target entity description: Newton is the vehicle registration code used on license plates issued in Newton County, Georgia.
  • A. Newton
    Newton is a small settlement in West Lothian, Scotland, known primarily as a residential village within the Edinburgh commuter belt.
  • B. Newton
    Newton is a small Midwestern town that later became known as Rensselaer in Indiana, United States.
  • C. Newton
    Newton is a suburban city in Massachusetts known for its residential neighborhoods, strong public schools, and proximity to Boston.
  • D. Newton
    Newton is a small city in central Iowa known historically for its manufacturing industry, particularly as the former headquarters of the Maytag Corporation.
  • E. Newton
    Newton is a large, primarily residential planning area in eastern Singapore known for its food centre and proximity to the Orchard Road shopping district.
  • F. None of above. chosen

Provenance (5 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_69d8278775fc8190b0802d22ca2f495d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6124e23481909e5132a40a1d8624 completed April 14, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf21f8c8819097ff26e6bb345b52 completed May 7, 2026, 6:51 p.m.
NEDg Description generation batch_69fce0cc78e881909090ac42a97ebb12 completed May 7, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_69fce1f53a8881909fd1258729a9879d completed May 7, 2026, 7:03 p.m.
Created at: April 10, 2026, 12:56 a.m.