Triple

T5608889
Position Surface form Disambiguated ID Type / Status
Subject Leonding E147302 entity
Predicate adjacentTo P224 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: [Leonding, adjacentTo, Linz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linz
Context triple: [Leonding, adjacentTo, 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_69c0090500f881908374285baf0ac46f completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020fe7ee0819088ced51afd9a4f93 completed March 22, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c107b36b3c819084d7e8fda4de74b7 completed March 23, 2026, 9:28 a.m.
Created at: March 22, 2026, 3:39 p.m.