Triple

T15937195
Position Surface form Disambiguated ID Type / Status
Subject Kaisermühlen E386467 entity
Predicate near P350 FINISHED
Object Prater E281300 NE FINISHED

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: Prater | Statement: [Kaisermühlen, near, Prater]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prater
Context triple: [Kaisermühlen, near, Prater]
  • A. Prater
    Prater is a surname most notably associated with American soul singer Dave Prater, one half of the duo Sam & Dave.
  • B. Prater
    Prater is a large public park and historic amusement area in Vienna, Austria, best known for its iconic Giant Ferris Wheel and extensive green spaces.
  • C. Praza de Praterías
    Praza de Praterías is a historic square in Santiago de Compostela’s old town, known for its Baroque architecture and its location beside the cathedral.
  • D. Praterinsel
    Praterinsel is a small island in the Isar River in central Munich, known for its cultural events, historic buildings, and riverside recreation.
  • E. Vienna Prater chosen
    Vienna Prater is a historic amusement park and large public leisure area in Vienna, Austria, best known for its iconic Giant Ferris Wheel and traditional fairground attractions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156ab7f548190b2d1aafa0e6d2c24 completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5b8121881909b15bf6451d3d3a8 completed May 9, 2026, 10:31 p.m.
Created at: April 10, 2026, 4:53 a.m.