Triple

T9689754
Position Surface form Disambiguated ID Type / Status
Subject Blackcomb E234506 entity
Predicate relatedProject P2830 FINISHED
Object Vienna
Vienna is the capital city of Austria, renowned for its imperial history, classical music heritage, and rich cultural and architectural landmarks.
 E7023 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: Vienna | Statement: [Blackcomb, relatedProject, Vienna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vienna
Context triple: [Blackcomb, relatedProject, Vienna]
  • A. Vienna
    Vienna is the capital city of Austria, renowned for its rich imperial history, classical music heritage, and vibrant cultural and intellectual life.
  • B. Vienna
    Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • C. Vienna
    Vienna is the strong-willed saloon owner and central female protagonist in the 1954 Western film "Johnny Guitar."
  • D. 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.
  • E. 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.
  • 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: Vienna
Triple: [Blackcomb, relatedProject, Vienna]
Generated description
Vienna is the capital city of Austria, renowned for its imperial history, classical music heritage, and rich cultural and architectural landmarks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vienna
Target entity description: Vienna is the capital city of Austria, renowned for its imperial history, classical music heritage, and rich cultural and architectural landmarks.
  • A. Vienna chosen
    Vienna is the capital city of Austria, renowned for its rich imperial history, classical music heritage, and vibrant cultural and intellectual life.
  • B. 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.
  • C. Vienna
    Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • D. Vienna
    Vienna is the strong-willed saloon owner and central female protagonist in the 1954 Western film "Johnny Guitar."
  • E. 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.
  • F. None of above.

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_69ca84ca73208190957a900c8543bdcc completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d02b20881909d7c0d5d6aaafcb0 completed April 1, 2026, 10:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcb78e4c8190aaa55de453789168 completed April 5, 2026, 1:36 a.m.
NEDg Description generation batch_69d1bd42e3888190b13970710a9620d7 completed April 5, 2026, 1:39 a.m.
NED2 Entity disambiguation (via description) batch_69d1bdd5ec94819083edd1cb2c9598a0 completed April 5, 2026, 1:41 a.m.
Created at: March 30, 2026, 8:17 p.m.