Triple

T130495
Position Surface form Disambiguated ID Type / Status
Subject University of Zurich E2643 entity
Predicate city P40 FINISHED
Object Zurich E13407 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 | Statement: [University of Zurich, city, Zurich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zurich
Context triple: [University of Zurich, city, Zurich]
  • A. Zurich chosen
    Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
  • B. Geneva
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • C. Basel-Stadt
    Basel-Stadt is a small, urban Swiss canton centered on the city of Basel, a major cultural and economic hub in northwestern Switzerland.
  • D. Neuchâtel
    Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
  • E. Solothurn
    Solothurn is a canton in northwestern Switzerland known for its historic baroque town of the same name and its location along the Aare River.
  • 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_69a2520c0f3481908b0ed054a2fca8d0 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a257845c548190bfb49409988d1c57 completed Feb. 28, 2026, 2:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69a358763c10819085252de003a45435 completed Feb. 28, 2026, 9:04 p.m.
Created at: Feb. 28, 2026, 2:30 a.m.