Triple

T19335310
Position Surface form Disambiguated ID Type / Status
Subject Vogelsbergkreis E483606 entity
Predicate borders P224 FINISHED
Object Marburg-Biedenkopf 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: Marburg-Biedenkopf | Statement: [Vogelsbergkreis, borders, Marburg-Biedenkopf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marburg-Biedenkopf
Context triple: [Vogelsbergkreis, borders, Marburg-Biedenkopf]
  • A. Marburg-Biedenkopf chosen
    Marburg-Biedenkopf is a rural district in the German state of Hesse, centered around the university city of Marburg and known for its mix of historic towns and natural landscapes.
  • B. Ruppichteroth
    Ruppichteroth is a small municipality in western Germany’s North Rhine-Westphalia region, characterized by its rural setting and proximity to the metropolitan area of Cologne-Bonn.
  • C. Königstein im Taunus
    Königstein im Taunus is a historic spa and resort town in Hesse, Germany, known for its scenic location in the Taunus mountains and its medieval castle ruins.
  • D. Felsberg
    Felsberg is a settlement located in the historical region of Westphalia in western Germany.
  • E. Meinisberg
    Meinisberg is a small municipality in the canton of Bern in Switzerland, situated near the city of Biel/Bienne.
  • 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.