Triple

T13205035
Position Surface form Disambiguated ID Type / Status
Subject Old Town of Zurich E314337 entity
Predicate contains P35 FINISHED
Object Zurich Town Hall E349671 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: Zurich Town Hall | Statement: [Old Town of Zurich, contains, Zurich Town Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zurich Town Hall
Context triple: [Old Town of Zurich, contains, Zurich Town Hall]
  • A. Stadthaus Zürich chosen
    Stadthaus Zürich is the historic city hall building in Zurich that serves as the central seat of the city’s political administration and government.
  • B. Basel Town Hall
    Basel Town Hall is a historic Renaissance-style government building in Basel, Switzerland, serving as the seat of the canton’s political authorities.
  • C. Geneva City Hall
    Geneva City Hall is the historic seat of the municipal government of Geneva, Switzerland, known for hosting important political meetings and international diplomatic events.
  • D. Geneva City Hall
    Geneva City Hall is the municipal government building serving the city of Geneva in Ontario County, New York.
  • E. Leonberg town hall
    Leonberg town hall is the main municipal administrative building and local government seat of the town of Leonberg in Baden-Württemberg, Germany.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c9b0cf08190a1d71cc94139539d completed April 10, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f60eee288190bdb3ed6110394e48 completed May 3, 2026, 7:15 a.m.
Created at: April 9, 2026, 9:17 p.m.