Triple

T5251132
Position Surface form Disambiguated ID Type / Status
Subject Prowers County, Colorado E118588 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object Prowers
Prowers is the vehicle registration code used to identify motor vehicles registered in Prowers County, Colorado.
E507162 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: Prowers | Statement: [Prowers County, Colorado, vehicleRegistrationCode, Prowers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prowers
Context triple: [Prowers County, Colorado, vehicleRegistrationCode, Prowers]
  • A. Pendleton
    Pendleton is an inner-city district of Salford in Greater Manchester, England, known for its mix of residential areas, retail developments, and post-war social housing.
  • B. Paxton
    Paxton is a small rural village in the Scottish Borders region of southeastern Scotland.
  • C. Paxton
    Paxton is a surname most prominently associated with the late American actor and filmmaker Bill Paxton, known for his roles in films like "Twister," "Aliens," and "Titanic."
  • D. Evarts
    Evarts is a surname most notably associated with William M. Evarts, a prominent 19th-century American lawyer, statesman, and U.S. Secretary of State.
  • E. Daggett
    Daggett is a small unincorporated desert community in San Bernardino County, California, historically known as a railroad and mining town along major transportation routes.
  • 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: Prowers
Triple: [Prowers County, Colorado, vehicleRegistrationCode, Prowers]
Generated description
Prowers is the vehicle registration code used to identify motor vehicles registered in Prowers County, Colorado.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Prowers
Target entity description: Prowers is the vehicle registration code used to identify motor vehicles registered in Prowers County, Colorado.
  • A. Pendleton
    Pendleton is an inner-city district of Salford in Greater Manchester, England, known for its mix of residential areas, retail developments, and post-war social housing.
  • B. Paxton
    Paxton is a small rural village in the Scottish Borders region of southeastern Scotland.
  • C. Paxton
    Paxton is a surname most prominently associated with the late American actor and filmmaker Bill Paxton, known for his roles in films like "Twister," "Aliens," and "Titanic."
  • D. Evarts
    Evarts is a surname most notably associated with William M. Evarts, a prominent 19th-century American lawyer, statesman, and U.S. Secretary of State.
  • E. Daggett
    Daggett is a small unincorporated desert community in San Bernardino County, California, historically known as a railroad and mining town along major transportation routes.
  • 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_69bd446978108190bb5f9c5c23d93f88 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b7b840881908bb1ecb8a0047382 completed March 20, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe7005308190a659efbd779c314b completed March 21, 2026, 8:24 p.m.
NEDg Description generation batch_69beff4322308190b252820e7213f05e completed March 21, 2026, 8:27 p.m.
NED2 Entity disambiguation (via description) batch_69beffe02d208190b857d6aaa4d85dae completed March 21, 2026, 8:30 p.m.
Created at: March 20, 2026, 1:50 p.m.