Triple

T3075437
Position Surface form Disambiguated ID Type / Status
Subject University of Marburg E64123 entity
Predicate region P40 FINISHED
Object Central Hesse E109575 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: Central Hesse | Statement: [University of Marburg, region, Central Hesse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Central Hesse
Context triple: [University of Marburg, region, Central Hesse]
  • A. Middle Hesse chosen
    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.
  • B. South Hesse
    South Hesse is a region in the southern part of the German state of Hesse that includes major urban and economic centers such as Darmstadt and the Rhine-Main area.
  • C. Hesse-Kassel
    Hesse-Kassel was a German principality known for supplying large numbers of Hessian mercenary troops to fight alongside the British during the American Revolutionary War.
  • D. Northern Hesse region
    The Northern Hesse region is a historical area in central Germany that once formed part of the territorial domain of the Prince of Waldeck.
  • E. Ansbach region
    The Ansbach region is an area in the German state of Bavaria, historically part of Franconia and known for its distinct East Franconian dialect and 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_69ad857a8aec8190bfdfd9c14554ac5a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada150d8e08190bde5f68e800e8feb completed March 8, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20357f8c48190b6874f7596f30052 completed March 12, 2026, 12:05 a.m.
Created at: March 8, 2026, 3:02 p.m.