Triple

T10204248
Position Surface form Disambiguated ID Type / Status
Subject Province of Potenza E238961 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object PZ
PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
 E846613 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: PZ | Statement: [Province of Potenza, vehicleRegistrationCode, PZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PZ
Context triple: [Province of Potenza, vehicleRegistrationCode, PZ]
  • A. PZ
    PZ is the vehicle registration code used on license plates for vehicles registered in the Preveza regional unit of Greece.
  • B. PZ
    PZ is the IATA airline designator assigned to LATAM Airlines Paraguay, the Paraguayan branch of the LATAM Airlines Group.
  • C. ZP
    ZP is a German vehicle registration code assigned to the Erzgebirgskreis district in the state of Saxony.
  • D. PZH
    PZH is the IATA airport code for Zhob Airport in Balochistan, Pakistan.
  • E. PZB
    PZB is a German train protection system that automatically supervises train speeds and signal observance to prevent accidents such as passing signals at danger.
  • 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: PZ
Triple: [Province of Potenza, vehicleRegistrationCode, PZ]
Generated description
PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PZ
Target entity description: PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
  • A. PZ
    PZ is the vehicle registration code used on license plates for vehicles registered in the Preveza regional unit of Greece.
  • B. PZ
    PZ is the IATA airline designator assigned to LATAM Airlines Paraguay, the Paraguayan branch of the LATAM Airlines Group.
  • C. ZP
    ZP is a German vehicle registration code assigned to the Erzgebirgskreis district in the state of Saxony.
  • D. PZH
    PZH is the IATA airport code for Zhob Airport in Balochistan, Pakistan.
  • E. PZB
    PZB is a German train protection system that automatically supervises train speeds and signal observance to prevent accidents such as passing signals at danger.
  • 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_69ca84e1ea088190b38162e43d4cfa8f completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdeed6fd0081908f8afad1ef4c6bff completed April 2, 2026, 4:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69d318026ee88190961288fdbde73b08 completed April 6, 2026, 2:18 a.m.
NEDg Description generation batch_69d318a95450819086cd07610de39a55 completed April 6, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_69d319593c908190adc43bc2a213211f completed April 6, 2026, 2:24 a.m.
Created at: March 30, 2026, 9:14 p.m.