Triple

T4169070
Position Surface form Disambiguated ID Type / Status
Subject Worldwide Universities Network E84515 entity
Predicate abbreviation P43 FINISHED
Object WUN
WUN is a global consortium of research-intensive universities that collaborate on international education and research initiatives.
 E416789 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: [Worldwide Universities Network, abbreviation, WUN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WUN
Context triple: [Worldwide Universities Network, abbreviation, WUN]
  • A. WUN
    WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • B. WU
    WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
  • C. WU
    WU is a leading European university in Vienna specializing in economics, business, and social sciences.
  • D. WÜ
    WÜ is the vehicle registration code for the city and district of Würzburg in the Lower Franconia region of Bavaria, Germany.
  • E. WUH
    WUH is the IATA airport code for Wuhan Tianhe International Airport, the main air gateway serving Wuhan in central China.
  • 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: [Worldwide Universities Network, abbreviation, WUN]
Generated description
WUN is a global consortium of research-intensive universities that collaborate on international education and research initiatives.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WUN
Target entity description: WUN is a global consortium of research-intensive universities that collaborate on international education and research initiatives.
  • A. WUN
    WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • B. WU
    WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
  • C. WU
    WU is a leading European university in Vienna specializing in economics, business, and social sciences.
  • D. WÜ
    WÜ is the vehicle registration code for the city and district of Würzburg in the Lower Franconia region of Bavaria, Germany.
  • E. WUH
    WUH is the IATA airport code for Wuhan Tianhe International Airport, the main air gateway serving Wuhan in central China.
  • 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_69aed932cab48190b80ffe35f7029ae1 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02c730b081908b19e6a4aea1549b completed March 9, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f4c2c988190959496cc0cc31cac completed March 14, 2026, 3:31 p.m.
NEDg Description generation batch_69b57fe89ed0819089d7e56568755b1c completed March 14, 2026, 3:34 p.m.
NED2 Entity disambiguation (via description) batch_69b5805cb7e88190b2f6ed6a18de9319 completed March 14, 2026, 3:35 p.m.
Created at: March 9, 2026, 3:44 p.m.