Triple

T2917976
Position Surface form Disambiguated ID Type / Status
Subject Berggarten E78650 entity
Predicate nearbyAttraction P3449 FINISHED
Object Georgengarten E79281 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: Georgengarten | Statement: [Berggarten, nearbyAttraction, Georgengarten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Georgengarten
Context triple: [Berggarten, nearbyAttraction, Georgengarten]
  • A. Georgengarten chosen
    Georgengarten is a large English-style landscape park in Hanover, Germany, known for its expansive lawns, tree-lined avenues, and integration into the historic Herrenhausen Gardens ensemble.
  • B. Hofgarten
    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.
  • C. Tiergarten
    Tiergarten is a large central park in Berlin known for its expansive green spaces, monuments, and cultural landmarks.
  • D. Berggarten
    Berggarten is a historic botanical garden in Hanover, Germany, renowned for its diverse plant collections and greenhouses.
  • E. Burggarten
    Burggarten is a historic public park in central Vienna, Austria, known for its landscaped gardens, statues, and proximity to the former imperial Hofburg Palace.
  • 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_69ad8b0c2ad081909ff87050ae542bb9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad96a41b4c81909d8ace8ab270ed3c completed March 8, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0562c5b5081908026b3f590b03aca completed March 10, 2026, 5:34 p.m.
Created at: March 8, 2026, 2:54 p.m.