Triple

T1191232
Position Surface form Disambiguated ID Type / Status
Subject Vienna University of Economics and Business E25364 entity
Predicate shortName P43 FINISHED
Object WU
WU is a leading European university in Vienna specializing in economics, business, and social sciences.
 E136776 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: WU | Statement: [Vienna University of Economics and Business, shortName, WU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WU
Context triple: [Vienna University of Economics and Business, shortName, WU]
  • A. WUH
    WUH is the IATA airport code for Wuhan Tianhe International Airport, the main air gateway serving Wuhan in central China.
  • B. WUG
    WUG is the vehicle registration code for the Weißenburg-Gunzenhausen district in Middle Franconia, Bavaria, Germany.
  • C. 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.
  • D. UUWW
    UUWW is the ICAO airport code assigned to Vnukovo International Airport in Moscow, Russia.
  • 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: WU
Triple: [Vienna University of Economics and Business, shortName, WU]
Generated description
WU is a leading European university in Vienna specializing in economics, business, and social sciences.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WU
Target entity description: WU is a leading European university in Vienna specializing in economics, business, and social sciences.
  • A. WUH
    WUH is the IATA airport code for Wuhan Tianhe International Airport, the main air gateway serving Wuhan in central China.
  • B. WUG
    WUG is the vehicle registration code for the Weißenburg-Gunzenhausen district in Middle Franconia, Bavaria, Germany.
  • C. 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.
  • D. UUWW
    UUWW is the ICAO airport code assigned to Vnukovo International Airport in Moscow, Russia.
  • 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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd74e2c08190b4a48425f94addaa completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac764ea588819082f7d5d0e44e1211 completed March 7, 2026, 7:02 p.m.
NEDg Description generation batch_69ac76e1b430819092669c6e83d7a62c completed March 7, 2026, 7:05 p.m.
NED2 Entity disambiguation (via description) batch_69ac7768daa4819082a07fa755ce7364 completed March 7, 2026, 7:07 p.m.
Created at: March 1, 2026, 7:45 p.m.