Triple

T4003339
Position Surface form Disambiguated ID Type / Status
Subject Wesel E89464 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object WES
WES is the vehicle registration code used on license plates for vehicles registered in the Wesel district of Germany.
E407396 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: WES | Statement: [Wesel, vehicleRegistrationCode, WES]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WES
Context triple: [Wesel, vehicleRegistrationCode, WES]
  • A. WES
    WES is the standard abbreviation for the Westchester Knicks, the NBA G League affiliate of the New York Knicks.
  • B. WES
    WES is a commuter rail service in the Portland, Oregon metropolitan area that connects Beaverton and Wilsonville.
  • C. WES
    WES is the historic Chapman code used in genealogical records to represent the former English county of Westmorland.
  • D. WST
    WST is the commonly used abbreviation for the World Snooker Tour, the professional circuit for elite snooker players worldwide.
  • E. ESU
    ESU is a specialized police emergency response unit that handles high-risk situations such as tactical operations, rescues, and hazardous incidents.
  • 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: WES
Triple: [Wesel, vehicleRegistrationCode, WES]
Generated description
WES is the vehicle registration code used on license plates for vehicles registered in the Wesel district of Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: WES
Target entity description: WES is the vehicle registration code used on license plates for vehicles registered in the Wesel district of Germany.
  • A. WES
    WES is a commuter rail service in the Portland, Oregon metropolitan area that connects Beaverton and Wilsonville.
  • B. WES
    WES is the standard abbreviation for the Westchester Knicks, the NBA G League affiliate of the New York Knicks.
  • C. WES
    WES is the historic Chapman code used in genealogical records to represent the former English county of Westmorland.
  • D. WST
    WST is the commonly used abbreviation for the World Snooker Tour, the professional circuit for elite snooker players worldwide.
  • E. ESU
    ESU is a specialized police emergency response unit that handles high-risk situations such as tactical operations, rescues, and hazardous incidents.
  • 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_69aed9585e788190bec2d39deba3750f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa5de98c8190a95b21a75fffdef3 completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c61bad48190a5115dbd4a3457d6 completed March 14, 2026, 11:54 a.m.
NEDg Description generation batch_69b54cf3da208190aa844c9ea66354fe completed March 14, 2026, 11:56 a.m.
NED2 Entity disambiguation (via description) batch_69b55159dc288190a63d5f5164b73bbb completed March 14, 2026, 12:15 p.m.
Created at: March 9, 2026, 3:34 p.m.