Triple

T3336788
Position Surface form Disambiguated ID Type / Status
Subject Limmat E70156 entity
Predicate flowsPast P4996 FINISHED
Object Old Town of Zurich E314337 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: Old Town of Zurich | Statement: [Limmat, flowsPast, Old Town of Zurich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Old Town of Zurich
Context triple: [Limmat, flowsPast, Old Town of Zurich]
  • A. Old Town of Zurich chosen
    The Old Town of Zurich is the historic city center characterized by medieval streets, riverside promenades, and well-preserved architecture, serving as a cultural and tourist heart of Zurich.
  • B. Old Town of Geneva
    The Old Town of Geneva is the city's historic center, characterized by its medieval streets, landmark St. Peter's Cathedral, and well-preserved architecture overlooking Lake Geneva.
  • C. St. Gallen
    St. Gallen is a historic city in northeastern Switzerland renowned for its UNESCO-listed Abbey of Saint Gall and rich textile heritage.
  • D. Winterthur, Switzerland
    Winterthur, Switzerland is a city in the canton of Zurich known for its rich industrial heritage, vibrant cultural scene, and numerous museums and gardens.
  • E. Grenchen
    Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bad97481909359e914d44a1a74 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a8ad1a8819081d7ad2a48e2c5b9 completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:12 p.m.