Triple

T17399915
Position Surface form Disambiguated ID Type / Status
Subject Theatinerkirche E423057 entity
Predicate nearbyLandmark P350 FINISHED
Object Hofgarten Munich 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: Hofgarten Munich | Statement: [Theatinerkirche, nearbyLandmark, Hofgarten Munich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hofgarten Munich
Context triple: [Theatinerkirche, nearbyLandmark, Hofgarten Munich]
  • A. Hofgarten chosen
    The Hofgarten is a historic Renaissance-style court garden in central Munich, known for its arcades, pavilions, and role as a popular public park and cultural venue.
  • B. Englischer Garten
    Englischer Garten is a large public park in Munich, Germany, renowned for its expansive green spaces, beer gardens, and riverside surfing on the Eisbach.
  • C. Volksgarten
    Volksgarten is a historic public park in central Vienna renowned for its formal rose gardens, neoclassical monuments, and location along the Ringstrasse.
  • D. Tiergarten
    Tiergarten is a large central park in Berlin known for its expansive green spaces, monuments, and cultural landmarks.
  • E. Karlsaue Park
    Karlsaue Park is a historic baroque landscape park in Kassel, Germany, known for its formal gardens, expansive meadows, and integration of art and architecture.
  • 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_69d889d710288190bf0f4762801fefae completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43ac0596481908c400916d5c1b971 completed April 19, 2026, 2:15 a.m.
Created at: April 10, 2026, 5:45 a.m.