Triple

T19632788
Position Surface form Disambiguated ID Type / Status
Subject Gmunden E471312 entity
Predicate hasLandmark P105 FINISHED
Object Schloss Ort 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: Schloss Ort | Statement: [Gmunden, hasLandmark, Schloss Ort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schloss Ort
Context triple: [Gmunden, hasLandmark, Schloss Ort]
  • A. Schloss Ort chosen
    Schloss Ort is a historic lakeside castle in Gmunden, Austria, renowned for its picturesque island setting on Lake Traunsee.
  • B. Schloss Berg
    Schloss Berg is a historic castle and former ducal residence located in the village of Berg in Bavaria, Germany, overlooking Lake Starnberg.
  • C. Schloss Niederaichbach
    Schloss Niederaichbach is a historic Bavarian castle and noble residence in Germany associated with European aristocratic families.
  • D. Schloss Vollrads
    Schloss Vollrads is a historic wine estate and castle in Germany’s Rheingau region, renowned for its centuries-old Riesling production and picturesque architecture.
  • E. Schloss Altenau
    Schloss Altenau was the original name of Mirabell Palace, a historic Baroque residence and garden complex in Salzburg, Austria.
  • 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_69d8e511f28481909f4bc3ea9191e54a completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6410449ec8190b8c20c0e09cd9156 completed April 20, 2026, 3:06 p.m.
Created at: April 10, 2026, 1:44 p.m.