Triple

T810872
Position Surface form Disambiguated ID Type / Status
Subject Middle Franconia E17540 entity
Predicate borders P224 FINISHED
Object Upper Palatinate E45581 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: Upper Palatinate | Statement: [Middle Franconia, borders, Upper Palatinate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Upper Palatinate
Context triple: [Middle Franconia, borders, Upper Palatinate]
  • A. Upper Palatinate chosen
    Upper Palatinate is a historical region in eastern Bavaria, Germany, known for its forests, rivers, and medieval towns near the Czech border.
  • B. Upper Bavaria
    Upper Bavaria is a southeastern administrative region of Germany known for including the city of Munich, the Bavarian Alps, and many of the state’s most famous cultural and natural landmarks.
  • 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 Franconia
    Middle Franconia is an administrative region in the German state of Bavaria, known for cities such as Nuremberg, Erlangen, and Fürth.
  • E. Lower Bavaria
    Lower Bavaria is an administrative region in southeastern Germany known for its rural landscapes, historic towns, and location along the Danube River.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab282fe48190a05ee97550843cd7 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac660a86d881908ae96a5492c9b9a2 completed March 7, 2026, 5:53 p.m.
Created at: March 1, 2026, 7:38 p.m.