Triple

T20838223
Position Surface form Disambiguated ID Type / Status
Subject Schutterwald E513018 entity
Predicate borderedBy P224 FINISHED
Object Meißenheim 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: Meißenheim | Statement: [Schutterwald, borderedBy, Meißenheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meißenheim
Context triple: [Schutterwald, borderedBy, Meißenheim]
  • A. Meißenheim chosen
    Meißenheim is a small municipality in southwestern Germany’s Baden-Württemberg region, situated within the Ortenau district near the Rhine River.
  • B. Münchberg
    Münchberg is a town in the Upper Franconia region of Bavaria, Germany, known historically for its textile industry and as a local commercial center.
  • C. Meisenthal
    Meisenthal is a village in northeastern France renowned for its historic glassmaking tradition and cultural heritage.
  • D. Tirschenreuth
    Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
  • E. Maschteich
    Maschteich is an artificial pond in Hanover, Germany, situated in the Maschpark near the New Town Hall and known for its scenic urban green setting.
  • 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_69e0b4cf62a88190bbf92351e9e57259 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c32928788190be8ca57923eefd7e completed April 21, 2026, 12:22 a.m.
Created at: April 16, 2026, 12:42 p.m.