Triple

T17454667
Position Surface form Disambiguated ID Type / Status
Subject James-Simon-Galerie E424997 entity
Predicate near P350 FINISHED
Object Lustgarten 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: Lustgarten | Statement: [James-Simon-Galerie, near, Lustgarten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lustgarten
Context triple: [James-Simon-Galerie, near, Lustgarten]
  • A. Lustgarten chosen
    Lustgarten is a historic public park and square on Berlin’s Museum Island, long used as a parade ground and gathering place.
  • B. Wildenberg
    Wildenberg is a small municipality in the Kelheim district of Lower Bavaria, Germany, known for its rural character and agricultural surroundings.
  • C. Rittersgrün
    Rittersgrün is a village in the Saxon Ore Mountains of Germany known historically for its role in regional mining and its traditional mountain culture.
  • D. Leingarten
    Leingarten is a municipality in the Heilbronn district of Baden-Württemberg, Germany, known for its wine-growing tradition and location near the city of Heilbronn.
  • E. Riedergarten
    Riedergarten is a historic public garden and popular green oasis located in the Bavarian city of Rosenheim, Germany.
  • 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4514129f08190ae7581d2915a0373 completed April 19, 2026, 3:51 a.m.
Created at: April 10, 2026, 5:47 a.m.