Triple

T7542785
Position Surface form Disambiguated ID Type / Status
Subject Province of Cuneo E178320 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object CN
CN is the vehicle registration code used on license plates for the Province of Cuneo in Italy.
 E671105 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: CN | Statement: [Province of Cuneo, vehicleRegistrationCode, CN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CN
Context triple: [Province of Cuneo, vehicleRegistrationCode, CN]
  • A. CN
    CN is a major Canadian freight railway company that operates an extensive rail network across Canada and into the United States.
  • B. CN
    CN is the commonly used abbreviation for Monaco’s National Council, the unicameral legislative body of the Principality.
  • C. CN
    CN is the vehicle registration code used for County Cavan in Ireland.
  • D. Simplified Chinese
    Simplified Chinese is a standardized form of written Chinese that uses characters with reduced strokes, primarily employed in mainland China and Singapore.
  • E. Zhong Wen
    Zhong Wen is the tough, determined police officer portrayed by Jackie Chan in the action film "Police Story 2013."
  • 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: CN
Triple: [Province of Cuneo, vehicleRegistrationCode, CN]
Generated description
CN is the vehicle registration code used on license plates for the Province of Cuneo in Italy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CN
Target entity description: CN is the vehicle registration code used on license plates for the Province of Cuneo in Italy.
  • A. CN
    CN is a major Canadian freight railway company that operates an extensive rail network across Canada and into the United States.
  • B. CN
    CN is the commonly used abbreviation for Monaco’s National Council, the unicameral legislative body of the Principality.
  • C. CN
    CN is the vehicle registration code used for County Cavan in Ireland.
  • D. Simplified Chinese
    Simplified Chinese is a standardized form of written Chinese that uses characters with reduced strokes, primarily employed in mainland China and Singapore.
  • E. Zhong Wen
    Zhong Wen is the tough, determined police officer portrayed by Jackie Chan in the action film "Police Story 2013."
  • 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_69c69f2be3888190a6667a27f8f195e9 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8762b048190a0b262f9cb3fe1b0 completed March 27, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84f1d1e148190be015c62ae1ea1e8 completed March 28, 2026, 9:58 p.m.
NEDg Description generation batch_69c84fe59f24819094e11378ed57963f completed March 28, 2026, 10:02 p.m.
NED2 Entity disambiguation (via description) batch_69c8506a7f4c8190be0f97e434bbeed7 completed March 28, 2026, 10:04 p.m.
Created at: March 27, 2026, 3:48 p.m.