Triple

T724093
Position Surface form Disambiguated ID Type / Status
Subject Fürth town hall E14683 entity
Predicate locatedIn P40 FINISHED
Object Middle Franconia E17540 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: Middle Franconia | Statement: [Fürth town hall, locatedIn, Middle Franconia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Middle Franconia
Context triple: [Fürth town hall, locatedIn, Middle Franconia]
  • A. Middle Franconia chosen
    Middle Franconia is an administrative region in the German state of Bavaria, known for cities such as Nuremberg, Erlangen, and Fürth.
  • B. Lower Franconia
    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.
  • C. 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.
  • D. Middle Hesse
    Middle Hesse is a central region of the German state of Hesse known for its mix of historic university towns, industrial centers, and rural landscapes.
  • E. Upper Palatinate
    Upper Palatinate is a historical region in eastern Bavaria, Germany, known for its forests, rivers, and medieval towns near the Czech border.
  • 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_69a4934c753c81909b309027e48b9b3a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5a6ab508190b70a05a9d77829a5 completed March 1, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a826c4a35081909903e42dfa56d582 completed March 4, 2026, 12:34 p.m.
Created at: March 1, 2026, 7:37 p.m.