Triple

T6807247
Position Surface form Disambiguated ID Type / Status
Subject Waiblingen E156338 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object WN
WN is the vehicle registration code used on license plates for the Waiblingen district in the German state of Baden-Württemberg.
 E619632 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: WN | Statement: [Waiblingen, vehicleRegistrationCode, WN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WN
Context triple: [Waiblingen, vehicleRegistrationCode, WN]
  • A. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • B. WM
    WM was the reporting mark for the Western Maryland Railway, a regional U.S. railroad that later became part of the Chessie System.
  • C. Wa
    Wa is a town in northwestern Ghana that serves as an administrative, commercial, and cultural hub for the surrounding region.
  • D. W
    W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
  • E. W
    The W is a local New York City Subway service that runs on the BMT Broadway Line in Manhattan and Queens, typically operating on weekdays.
  • 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: WN
Triple: [Waiblingen, vehicleRegistrationCode, WN]
Generated description
WN is the vehicle registration code used on license plates for the Waiblingen district in the German state of Baden-Württemberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WN
Target entity description: WN is the vehicle registration code used on license plates for the Waiblingen district in the German state of Baden-Württemberg.
  • A. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • B. WM
    WM was the reporting mark for the Western Maryland Railway, a regional U.S. railroad that later became part of the Chessie System.
  • C. Wa
    Wa is a town in northwestern Ghana that serves as an administrative, commercial, and cultural hub for the surrounding region.
  • D. W
    The W is a local New York City Subway service that runs on the BMT Broadway Line in Manhattan and Queens, typically operating on weekdays.
  • E. W
    W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
  • 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_69c68826e6a48190a3d220b541e639de completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d30a006081908996e31aa7ced0ac completed March 27, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71aa27cec81909f45911ffa44ea6f completed March 28, 2026, 12:02 a.m.
NEDg Description generation batch_69c71bb4dcf08190b3b333f6a282bd8a completed March 28, 2026, 12:07 a.m.
NED2 Entity disambiguation (via description) batch_69c71c4133908190a2b0a79475101666 completed March 28, 2026, 12:09 a.m.
Created at: March 27, 2026, 2:16 p.m.