Triple

T2069474
Position Surface form Disambiguated ID Type / Status
Subject Upper Franconia E45981 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object WUN
WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
 E230932 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: WUN | Statement: [Upper Franconia, hasVehicleRegistrationCode, WUN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WUN
Context triple: [Upper Franconia, hasVehicleRegistrationCode, WUN]
  • A. WU
    WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
  • B. WU
    WU is a leading European university in Vienna specializing in economics, business, and social sciences.
  • C. WUH
    WUH is the IATA airport code for Wuhan Tianhe International Airport, the main air gateway serving Wuhan in central China.
  • D. WUG
    WUG is the vehicle registration code for the Weißenburg-Gunzenhausen district in Middle Franconia, Bavaria, Germany.
  • E. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • 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: WUN
Triple: [Upper Franconia, hasVehicleRegistrationCode, WUN]
Generated description
WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WUN
Target entity description: WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • A. WU
    WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
  • B. WU
    WU is a leading European university in Vienna specializing in economics, business, and social sciences.
  • C. WUH
    WUH is the IATA airport code for Wuhan Tianhe International Airport, the main air gateway serving Wuhan in central China.
  • D. WUG
    WUG is the vehicle registration code for the Weißenburg-Gunzenhausen district in Middle Franconia, Bavaria, Germany.
  • E. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • 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_69a8891b38288190abd572ccad9b6928 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9f51a008190aead0173a9289204 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae27289eb081909bfbc9bf2cd14878 completed March 9, 2026, 1:49 a.m.
NEDg Description generation batch_69ae28c163088190818891302f7faa8e completed March 9, 2026, 1:56 a.m.
NED2 Entity disambiguation (via description) batch_69ae292a9d7481909acbc3a5f24ff0b9 completed March 9, 2026, 1:58 a.m.
Created at: March 4, 2026, 7:41 p.m.