Triple

T9540457
Position Surface form Disambiguated ID Type / Status
Subject Vilsbiburg E230142 entity
Predicate countrySubdivision P766 FINISHED
Object State of Bavaria E7752 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: State of Bavaria | Statement: [Vilsbiburg, countrySubdivision, State of Bavaria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: State of Bavaria
Context triple: [Vilsbiburg, countrySubdivision, State of Bavaria]
  • A. Bavaria chosen
    Bavaria is a historic region and federal state in southeastern Germany, known for its distinct cultural traditions, large size and population, and major cities such as Munich.
  • B. Baden-Württemberg
    Baden-Württemberg is a federal state in southwest Germany known for its strong economy, automotive industry, and cities like Stuttgart, Heidelberg, and Freiburg.
  • C. State of Bremen
    The State of Bremen is a small federal state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port facilities.
  • D. Bavaria and Carinthia
    Bavaria and Carinthia are neighboring regions of Germany and Austria, respectively, that meet along a portion of the Germany–Austria border.
  • E. Thuringia
    Thuringia is a federal state in central Germany known for its forested landscapes, historic cities like Weimar and Erfurt, and its rich cultural and intellectual heritage.
  • 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_69ca847b1b3081908f72bc932c17cc41 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98e695948190ab107fff38c57de7 completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18211c1408190806823e93932c64c completed April 4, 2026, 9:26 p.m.
Created at: March 30, 2026, 8:01 p.m.