Triple

T9833922
Position Surface form Disambiguated ID Type / Status
Subject Marburg-Biedenkopf E239053 entity
Predicate bordersWith P224 FINISHED
Object Waldeck-Frankenberg E806248 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: Waldeck-Frankenberg | Statement: [Marburg-Biedenkopf, bordersWith, Waldeck-Frankenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waldeck-Frankenberg
Context triple: [Marburg-Biedenkopf, bordersWith, Waldeck-Frankenberg]
  • A. Waldeck-Frankenberg chosen
    Waldeck-Frankenberg is a rural district in northern Hesse, Germany, known for its scenic landscapes, forests, and small historic towns.
  • B. Fürstenau
    Fürstenau is a small town in Lower Saxony, Germany, known for its historic center and location within the Osnabrück region.
  • C. Luxenberg
    Luxenberg is an alternative spelling or variant form of the name "Luxemburg," which can refer to the European country Luxembourg or the surname of notable individuals such as revolutionary Rosa Luxemburg.
  • D. Pfullendorf
    Pfullendorf is a historic town in the state of Baden-Württemberg in southern Germany, known for its well-preserved medieval old town.
  • E. Rolandseck
    Rolandseck is a district of Remagen in Rhineland-Palatinate, Germany, known for its scenic location on the Rhine and its historic railway station and cultural venues.
  • 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3385054819094145c96204e3f0d completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257601eec8190b7fa205cee61bb23 completed April 5, 2026, 12:36 p.m.
Created at: March 30, 2026, 8:32 p.m.