Triple

T5034007
Position Surface form Disambiguated ID Type / Status
Subject Vorarlberg E113376 entity
Predicate capital P234 FINISHED
Object Bregenz E207069 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: Bregenz | Statement: [Vorarlberg, capital, Bregenz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bregenz
Context triple: [Vorarlberg, capital, 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. 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.
  • 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. Wels
    Wels is a historic city in Upper Austria known as a former imperial residence and regional economic center.
  • E. Innsbruck
    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.
  • 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_69bd443775e48190a646ffbfc4334723 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73b68d8c8190b8e04fb406abdb0f completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba5b5f84819086b7af26923f0987 completed March 21, 2026, 3:33 p.m.
Created at: March 20, 2026, 1:36 p.m.