Triple

T817146
Position Surface form Disambiguated ID Type / Status
Subject Prince of Mindelheim E17672 entity
Predicate region P40 FINISHED
Object Swabia E64457 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: Swabia | Statement: [Prince of Mindelheim, region, Swabia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swabia
Context triple: [Prince of Mindelheim, region, Swabia]
  • A. Swabia (Bavaria) chosen
    Swabia (Bavaria) is an administrative region in southwestern Bavaria, Germany, known for its distinct Swabian cultural heritage and mix of industrial cities and rural landscapes.
  • B. Franconia
    Franconia is a historical region in northern Bavaria, Germany, known for its medieval towns, rich cultural heritage, and distinct Franconian identity within the German-speaking world.
  • C. Franconia
    Franconia is a suburban community in Fairfax County, Northern Virginia, known for its residential neighborhoods and proximity to Washington, D.C.
  • D. Duchy of Swabia
    The Duchy of Swabia was a major medieval stem duchy in southwestern Germany that played a key role in the politics and dynastic struggles of the Holy Roman Empire.
  • E. Bavaria
    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.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab621d2c819083f10bff4f66c482 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69adfb7b11fc8190b90361eed3b90f94 completed March 8, 2026, 10:43 p.m.
Created at: March 1, 2026, 7:38 p.m.