Triple

T7426378
Position Surface form Disambiguated ID Type / Status
Subject Red Bull Salzburg E171377 entity
Predicate hasRivalryWith P893 FINISHED
Object Austria Wien
Austria Wien is a major Viennese football club and one of Austria’s most successful and historic teams.
 E672182 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: Austria Wien | Statement: [Red Bull Salzburg, hasRivalryWith, Austria Wien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Austria Wien
Context triple: [Red Bull Salzburg, hasRivalryWith, Austria Wien]
  • A. Wien
    Wien is a German surname most notably borne by physicist Wilhelm Wien, known for his work on blackbody radiation and Wien's displacement law.
  • B. Vienna
    Vienna is the capital city of Austria, renowned for its rich imperial history, classical music heritage, and vibrant cultural and intellectual life.
  • C. Vienna
    Vienna is a suburban town in Fairfax County, Virginia, known for its residential neighborhoods, proximity to Washington, D.C., and access to the Washington Metro via the nearby Vienna/Fairfax–GMU station.
  • D. Vienna
    Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • E. Vienna
    Vienna is the strong-willed saloon owner and central female protagonist in the 1954 Western film "Johnny Guitar."
  • 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: Austria Wien
Triple: [Red Bull Salzburg, hasRivalryWith, Austria Wien]
Generated description
Austria Wien is a major Viennese football club and one of Austria’s most successful and historic teams.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Austria Wien
Target entity description: Austria Wien is a major Viennese football club and one of Austria’s most successful and historic teams.
  • A. Wien
    Wien is a German surname most notably borne by physicist Wilhelm Wien, known for his work on blackbody radiation and Wien's displacement law.
  • B. Vienna
    Vienna is the strong-willed saloon owner and central female protagonist in the 1954 Western film "Johnny Guitar."
  • C. Vienna
    Vienna is the capital city of Austria, renowned for its rich imperial history, classical music heritage, and vibrant cultural and intellectual life.
  • D. Vienna
    Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • E. Vienna
    Vienna is a suburban town in Fairfax County, Virginia, known for its residential neighborhoods, proximity to Washington, D.C., and access to the Washington Metro via the nearby Vienna/Fairfax–GMU station.
  • 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_69c68a63491881909281f73d4d5643bf completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f303eb988190ba9df7946fce1c86 completed March 27, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84ee844cc819081f44426658c7e27 completed March 28, 2026, 9:58 p.m.
NEDg Description generation batch_69c852da8c048190b2a0696f2e7b65c1 completed March 28, 2026, 10:14 p.m.
NED2 Entity disambiguation (via description) batch_69c853958b748190b4ecc9797389cc85 completed March 28, 2026, 10:17 p.m.
Created at: March 27, 2026, 3:12 p.m.