Triple

T810892
Position Surface form Disambiguated ID Type / Status
Subject Middle Franconia E17540 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object WUG
WUG is the vehicle registration code for the Weißenburg-Gunzenhausen district in Middle Franconia, Bavaria, Germany.
 E97823 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: WUG | Statement: [Middle Franconia, hasVehicleRegistrationCode, WUG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WUG
Context triple: [Middle Franconia, hasVehicleRegistrationCode, WUG]
  • A. WUH
    WUH is the IATA airport code for Wuhan Tianhe International Airport, the main air gateway serving Wuhan in central China.
  • B. UUBW
    UUBW is the ICAO airport code for Zhukovsky International Airport, a major passenger and cargo airport serving the Moscow region in Russia.
  • C. UUWW
    UUWW is the ICAO airport code assigned to Vnukovo International Airport in Moscow, Russia.
  • D. WNJU
    WNJU is a Spanish-language television station serving the New York City metropolitan area and acting as the Telemundo network’s local outlet.
  • E. WY
    WY is the New York Stock Exchange ticker symbol for Weyerhaeuser Company, one of the world’s largest private owners of timberlands and a major forest products company.
  • 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: WUG
Triple: [Middle Franconia, hasVehicleRegistrationCode, WUG]
Generated description
WUG is the vehicle registration code for the Weißenburg-Gunzenhausen district in Middle Franconia, Bavaria, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WUG
Target entity description: WUG is the vehicle registration code for the Weißenburg-Gunzenhausen district in Middle Franconia, Bavaria, Germany.
  • A. WUH
    WUH is the IATA airport code for Wuhan Tianhe International Airport, the main air gateway serving Wuhan in central China.
  • B. UUBW
    UUBW is the ICAO airport code for Zhukovsky International Airport, a major passenger and cargo airport serving the Moscow region in Russia.
  • C. UUWW
    UUWW is the ICAO airport code assigned to Vnukovo International Airport in Moscow, Russia.
  • D. WNJU
    WNJU is a Spanish-language television station serving the New York City metropolitan area and acting as the Telemundo network’s local outlet.
  • E. WY
    WY is the New York Stock Exchange ticker symbol for Weyerhaeuser Company, one of the world’s largest private owners of timberlands and a major forest products company.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab282fe48190a05ee97550843cd7 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8869888190a95857546dfae5b3 completed March 3, 2026, 11:23 p.m.
NEDg Description generation batch_69a78e436c048190b31b53fff1c48f1d completed March 4, 2026, 1:43 a.m.
NED2 Entity disambiguation (via description) batch_69a78eb80f6081908257889efaff6d33 completed March 4, 2026, 1:45 a.m.
Created at: March 1, 2026, 7:38 p.m.