Triple

T1839121
Position Surface form Disambiguated ID Type / Status
Subject Inn E41132 entity
Predicate flowsThrough P225 FINISHED
Object Innsbruck E110788 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: Innsbruck | Statement: [Inn, flowsThrough, Innsbruck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Innsbruck
Context triple: [Inn, flowsThrough, Innsbruck]
  • A. Innsbruck chosen
    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.
  • B. Salzburg
    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.
  • C. Linz
    Linz is a major Austrian city known for its industrial heritage, vibrant cultural scene, and location along the Danube River.
  • D. Bregenz
    Bregenz is an Austrian city on the eastern shore of Lake Constance, known for its lakeside setting, cultural festivals, and contemporary art and architecture.
  • E. Wels
    Wels is a historic city in Upper Austria known as a former imperial residence and regional economic center.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb03b3eb08190ae68d8476fc89c7f completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1c482908190b940497fc5d5db60 completed March 8, 2026, 7:45 p.m.
Created at: March 4, 2026, 7:33 p.m.