Triple

T19462396
Position Surface form Disambiguated ID Type / Status
Subject Salzburg Hauptbahnhof E486905 entity
Predicate connectsTo P845 FINISHED
Object Graz NE NERFINISHED

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: Graz | Statement: [Salzburg Hauptbahnhof, connectsTo, Graz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Graz
Context triple: [Salzburg Hauptbahnhof, connectsTo, Graz]
  • A. Graz chosen
    Graz is Austria’s second-largest city, known for its well-preserved medieval old town and historic role as a center of science and education.
  • B. Villach
    Villach is a historic city in southern Austria known for its Alpine setting, thermal spas, and role as a regional transport and cultural hub.
  • C. Klagenfurt
    Klagenfurt is the capital city of the Austrian state of Carinthia, known for its historic old town and proximity to Lake Wörthersee.
  • D. 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.
  • 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 (2 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633cd6c148190933b4d6bfe84cbe1 completed April 20, 2026, 2:10 p.m.
Created at: April 10, 2026, 1:38 p.m.