Triple

T19335334
Position Surface form Disambiguated ID Type / Status
Subject Vogelsbergkreis E483606 entity
Predicate hasHighestPoint P210 FINISHED
Object Taufstein NE NERFINISHED

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: Taufstein | Statement: [Vogelsbergkreis, hasHighestPoint, Taufstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taufstein
Context triple: [Vogelsbergkreis, hasHighestPoint, Taufstein]
  • A. Taufstein chosen
    Taufstein is a prominent hill in the Vogelsberg mountain range in Hesse, Germany, known for its basalt formations and surrounding forested landscape.
  • B. Eibenberg
    Eibenberg is a small locality that forms one of the subdivisions of the municipality of Burkhardtsdorf in Saxony, Germany.
  • C. Heiligenberg
    Heiligenberg is a prominent hill overlooking Heidelberg in Germany, known for its historical ruins and cultural sites.
  • D. Hünenberg
    Hünenberg is a municipality in the canton of Zug in central Switzerland, known for its residential character and location near Lake Zug.
  • E. Rorschacherberg
    Rorschacherberg is a municipality in the canton of St. Gallen in northeastern Switzerland, situated above Lake Constance with views over the lake and surrounding region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d13e3c81909d91d1d5ec37c095 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e61644b80c819080f9bca086424a36 completed April 20, 2026, 12:04 p.m.
Created at: April 10, 2026, 1:33 p.m.