Triple

T18481460
Position Surface form Disambiguated ID Type / Status
Subject Austrian Autobahn network E451568 entity
Predicate servesCity P82 FINISHED
Object Bregenz 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: Bregenz | Statement: [Austrian Autobahn network, servesCity, Bregenz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bregenz
Context triple: [Austrian Autobahn network, servesCity, Bregenz]
  • A. Bregenz chosen
    Bregenz is an Austrian city on the eastern shore of Lake Constance, known for its lakeside setting, cultural festivals, and contemporary art and architecture.
  • B. Bludenz
    Bludenz is a small alpine town in western Austria known as a regional hub for skiing, hiking, and chocolate production.
  • C. Feldkirch
    Feldkirch is a historic medieval town in western Austria near the borders with Switzerland and Liechtenstein, known for its well-preserved old town and the hilltop Schattenburg castle.
  • D. Merano
    Merano is a historic spa and resort town in northern Italy known for its mild climate, Alpine scenery, and blend of Italian and Austrian cultural influences.
  • E. 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.
  • 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_69d8d38465a0819099b9b42d2a662ac1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e531d3d13c81909c52d797360b840a completed April 19, 2026, 7:49 p.m.
Created at: April 10, 2026, 11:35 a.m.