Triple

T20043588
Position Surface form Disambiguated ID Type / Status
Subject Rastatt district E497493 entity
Predicate contains P35 FINISHED
Object Rheinmünster 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: Rheinmünster | Statement: [Rastatt district, contains, Rheinmünster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rheinmünster
Context triple: [Rastatt district, contains, Rheinmünster]
  • A. Rheinmünster chosen
    Rheinmünster is a municipality in the Rastatt district of Baden-Württemberg, Germany, situated near the Rhine River and known for its proximity to Karlsruhe/Baden-Baden Airport.
  • B. Monheim am Rhein
    Monheim am Rhein is a town in North Rhine-Westphalia, Germany, situated along the Rhine River and known for its strong local economy and family-friendly urban development.
  • C. Winsum
    Winsum is a historic village and former municipality in the Dutch province of Groningen, known for its old churches, windmills, and picturesque canals.
  • D. Heinsberg
    Heinsberg is a town in western Germany’s North Rhine-Westphalia near the Dutch border, known as the administrative center of the Heinsberg district.
  • E. Erftstadt
    Erftstadt is a town in the Rhein-Erft district of North Rhine-Westphalia, Germany, located southwest of Cologne and known for its mix of historic villages and suburban residential areas.
  • 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_69da627278c88190babe4297a9df1236 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662ed59bc8190a9ff25493e500ebb completed April 20, 2026, 5:31 p.m.
Created at: April 11, 2026, 3:37 p.m.