Triple

T6992953
Position Surface form Disambiguated ID Type / Status
Subject University Hospital Würzburg E162128 entity
Predicate region P40 FINISHED
Object Lower Franconia E47272 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: Lower Franconia | Statement: [University Hospital Würzburg, region, Lower Franconia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lower Franconia
Context triple: [University Hospital Würzburg, region, Lower Franconia]
  • A. Lower Franconia chosen
    Lower Franconia is an administrative region in northwestern Bavaria, Germany, known for its historic cities like Würzburg and its prominent wine-growing areas along the Main River.
  • B. Upper Franconia
    Upper Franconia is a region in northern Bavaria, Germany, known for its historic towns, dense concentration of breweries, and rich Franconian cultural heritage.
  • C. Middle Franconia
    Middle Franconia is an administrative region in the German state of Bavaria, known for cities such as Nuremberg, Erlangen, and Fürth.
  • D. Lower Bavaria
    Lower Bavaria is an administrative region in southeastern Germany known for its rural landscapes, historic towns, and location along the Danube River.
  • E. Mittelfranken
    Mittelfranken is a region in the German state of Bavaria known for its rich cultural traditions, historic cities, and significant contributions to the state's intangible cultural 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_69c68856d7808190ab33ee914640281b completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbc30fdc81909244d83c8178755c completed March 27, 2026, 7:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a161f088190bbc3c4e2815fa929 completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:32 p.m.