Triple

T1944863
Position Surface form Disambiguated ID Type / Status
Subject Kurt Schuschnigg E42038 entity
Predicate placeOfDeath P21 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: [Kurt Schuschnigg, placeOfDeath, Innsbruck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Innsbruck
Context triple: [Kurt Schuschnigg, placeOfDeath, 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. Kufstein
    Kufstein is a historic town in the Austrian state of Tyrol, known for its medieval fortress and picturesque setting in the Alps near the German border.
  • D. Linz
    Linz is a major Austrian city known for its industrial heritage, vibrant cultural scene, and location along the Danube River.
  • E. 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.
  • 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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb2ff43108190af37ad12d123dcba completed March 7, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fd173b881909fbd454fc9d7fabb completed March 9, 2026, 1:18 a.m.
Created at: March 4, 2026, 7:36 p.m.