Triple

T14609801
Position Surface form Disambiguated ID Type / Status
Subject Kurhessen E342926 entity
Predicate hasSubregion P285 FINISHED
Object Eschwege E241325 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: Eschwege | Statement: [Kurhessen, hasSubregion, Eschwege]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eschwege
Context triple: [Kurhessen, hasSubregion, Eschwege]
  • A. Eschwege chosen
    Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
  • B. Eschbach
    Eschbach is a village and district of the town of Usingen in the Hochtaunus region of Hesse, Germany.
  • C. Heuckewalde
    Heuckewalde is a small municipality in the German state of Saxony-Anhalt that forms part of the broader Leipzig metropolitan region.
  • D. Eckersbach
    Eckersbach is a district of the city of Zwickau in the German state of Saxony, known primarily as a residential area.
  • E. Weidach
    Weidach is a locality or district that forms part of the municipality of Blaustein in the state of Baden-Württemberg, Germany.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44f0dd48190a78662b5998a6722 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf0763ca081909fa8bcbdc46f2fac completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:25 a.m.