Triple

T19335332
Position Surface form Disambiguated ID Type / Status
Subject Vogelsbergkreis E483606 entity
Predicate containsMunicipality P852 FINISHED
Object Wartenberg (Hesse) 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: Wartenberg (Hesse) | Statement: [Vogelsbergkreis, containsMunicipality, Wartenberg (Hesse)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wartenberg (Hesse)
Context triple: [Vogelsbergkreis, containsMunicipality, Wartenberg (Hesse)]
  • A. Wartenberg (Hessen) chosen
    Wartenberg (Hessen) is a small municipality in the state of Hesse in central Germany.
  • B. Wörsbach
    Wörsbach is a small river in Hesse, Germany, that forms part of the local drainage system for the Idsteiner Senke basin.
  • C. Pfaffenweiler
    Pfaffenweiler is a small municipality in southwestern Germany’s Baden-Württemberg region, situated near Freiburg im Breisgau and known for its winegrowing and picturesque Black Forest surroundings.
  • D. Büttelborn
    Büttelborn is a municipality in the Groß-Gerau district of Hesse, Germany, situated in the Rhine-Main region near the city of Darmstadt.
  • E. Wiescheid
    Wiescheid is a district of the town of Langenfeld in North Rhine-Westphalia, Germany, characterized by its residential areas and proximity to surrounding green spaces.
  • 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.