Triple

T5198217
Position Surface form Disambiguated ID Type / Status
Subject Neu-Anif E117324 entity
Predicate partOf P40 FINISHED
Object Salzburg metropolitan area E19756 NE FINISHED

How this triple was built (2 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: Salzburg metropolitan area | Statement: [Neu-Anif, partOf, Salzburg metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salzburg metropolitan area
Context triple: [Neu-Anif, partOf, Salzburg metropolitan area]
  • A. Salzburg chosen
    Salzburg is a historic Austrian city on the Salzach River, renowned for its baroque architecture, Alpine setting, and as the birthplace of composer Wolfgang Amadeus Mozart.
  • B. Baden bei Wien
    Baden bei Wien is a historic spa town in eastern Austria renowned for its thermal springs, Biedermeier architecture, and proximity to Vienna.
  • C. Gmunden
    Gmunden is a picturesque town in Upper Austria known for its lakeside setting on the Traunsee and its historic ceramics industry.
  • D. Innsbruck
    Innsbruck is a city in western Austria known for its Alpine setting and winter sports facilities, and it later successfully hosted the Winter Olympics in 1964 and 1976.
  • E. Linz
    Linz is a major Austrian city known for its industrial heritage, vibrant cultural scene, and location along the Danube River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bd4462ed04819084fcb01eb9d2fa74 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a1f154481908be5d3c9cbbef92a completed March 20, 2026, 4:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfaf2bc1348190a92833a4c4e0e4cd completed March 22, 2026, 8:58 a.m.
Created at: March 20, 2026, 1:47 p.m.