Triple

T2582094
Position Surface form Disambiguated ID Type / Status
Subject Płońsk E57114 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object WPN
WPN is the vehicle registration code assigned to the town of Płońsk in Poland.
 E280220 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: WPN | Statement: [Płońsk, vehicleRegistrationCode, WPN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WPN
Context triple: [Płońsk, vehicleRegistrationCode, WPN]
  • A. WPN
    WPN is the station code used to identify White Plains station in transportation and scheduling systems.
  • B. WPK
    WPK is the ruling communist party of North Korea that dominates the country’s political system and state ideology.
  • C. WUN
    WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • D. WCP
    WCP is the abbreviation for the World Climate Programme, an international initiative focused on understanding and addressing global climate variability and change.
  • E. W8
    W8 is a central London postcode district covering the affluent Kensington area, known for its upscale residences, shops, and cultural institutions.
  • 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: WPN
Triple: [Płońsk, vehicleRegistrationCode, WPN]
Generated description
WPN is the vehicle registration code assigned to the town of Płońsk in Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WPN
Target entity description: WPN is the vehicle registration code assigned to the town of Płońsk in Poland.
  • A. WPN
    WPN is the station code used to identify White Plains station in transportation and scheduling systems.
  • B. WPK
    WPK is the ruling communist party of North Korea that dominates the country’s political system and state ideology.
  • C. WUN
    WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • D. WCP
    WCP is the abbreviation for the World Climate Programme, an international initiative focused on understanding and addressing global climate variability and change.
  • E. W8
    W8 is a central London postcode district covering the affluent Kensington area, known for its upscale residences, shops, and cultural institutions.
  • 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_69ab4a4dca6481908c301f8e317396e7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3c843bc8190837cea3441bf3ca1 completed March 7, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69af657cc2b08190a9055d6da7744851 completed March 10, 2026, 12:27 a.m.
NEDg Description generation batch_69af69a66078819084f341b052860751 completed March 10, 2026, 12:45 a.m.
NED2 Entity disambiguation (via description) batch_69af6a071f1c8190b2a707a0c98ddc94 completed March 10, 2026, 12:47 a.m.
Created at: March 6, 2026, 9:49 p.m.