Triple

T8010744
Position Surface form Disambiguated ID Type / Status
Subject České Budějovice E186483 entity
Predicate hasTwinTown P919 FINISHED
Object Linz E75219 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: Linz | Statement: [České Budějovice, hasTwinTown, Linz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linz
Context triple: [České Budějovice, hasTwinTown, Linz]
  • A. Linz chosen
    Linz is a major Austrian city known for its industrial heritage, vibrant cultural scene, and location along the Danube River.
  • B. Klagenfurt
    Klagenfurt is the capital city of the Austrian state of Carinthia, known for its historic old town and proximity to Lake Wörthersee.
  • C. St. Pölten
    St. Pölten is the capital city of the Austrian state of Lower Austria, known for its baroque architecture and role as a regional administrative and cultural center.
  • D. 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.
  • 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.
  • 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_69ca82abaffc8190ab8af79cdbc31ab3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3d70caf8819090a9f98025470c0d completed March 31, 2026, 3:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc93a8923081908402951d6490f8de completed April 1, 2026, 3:40 a.m.
Created at: March 30, 2026, 5:19 p.m.