Triple

T1092736
Position Surface form Disambiguated ID Type / Status
Subject Zurich Hauptbahnhof E24201 entity
Predicate serves P98 FINISHED
Object Zürich 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: Zürich | Statement: [Zurich Hauptbahnhof, serves, Zürich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zürich
Context triple: [Zurich Hauptbahnhof, serves, Zürich]
  • 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. 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.
  • C. Schaffhausen
    Schaffhausen is a historic town and capital of the canton of the same name in northern Switzerland, known for its well-preserved medieval old town and proximity to the Rhine Falls.
  • D. Geneva
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • E. Olten
    Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
  • 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_69a4940542308190ac2a0b1f730b7cfc completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b99bd06c8190bce1d77b0337b07c completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b367d6290081908f67eac0b7f6c53c completed March 13, 2026, 1:26 a.m.
Created at: March 1, 2026, 7:42 p.m.