Triple

T17799800
Position Surface form Disambiguated ID Type / Status
Subject Dagstuhl Castle E444390 entity
Predicate near P350 FINISHED
Object Losheim am See 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: Losheim am See | Statement: [Dagstuhl Castle, near, Losheim am See]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Losheim am See
Context triple: [Dagstuhl Castle, near, Losheim am See]
  • A. Losheim am See chosen
    Losheim am See is a municipality in the Saarland region of western Germany, known for its scenic reservoir and surrounding natural landscapes that attract tourists and outdoor enthusiasts.
  • B. Holzheim am Lech
    Holzheim am Lech is a small Bavarian municipality located in southern Germany’s Donau-Ries district near the River Lech.
  • C. Meimsheim
    Meimsheim is a village in the municipality of Brackenheim in the Heilbronn district of Baden-Württemberg, Germany.
  • D. Oberglauheim
    Oberglauheim is a village in Bavaria, Germany, that forms one of the local districts of the town of Höchstädt an der Donau.
  • E. Ettenheim
    Ettenheim is a historic small town in southwestern Germany’s Baden-Württemberg region, known for its well-preserved old town and location near the Black Forest.
  • 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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e487fe19dc8190b7e9dc96f39e0861 completed April 19, 2026, 7:45 a.m.
Created at: April 10, 2026, 10:13 a.m.