Triple

T755014
Position Surface form Disambiguated ID Type / Status
Subject Irchel campus E15534 entity
Predicate locatedIn 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: [Irchel campus, locatedIn, Zurich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zurich
Context triple: [Irchel campus, locatedIn, 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. Lausanne
    Lausanne is a major Swiss city on the shores of Lake Geneva, known for hosting the International Olympic Committee and its vibrant cultural and academic institutions.
  • D. St. Gallen
    St. Gallen is a historic city in northeastern Switzerland renowned for its UNESCO-listed Abbey of Saint Gall and rich textile heritage.
  • E. 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.
  • 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_69a493599a0081908da65f3407af1ef2 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a66820548190b373deb117187c2c completed March 1, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69adeaad456481908cf9fb412bdf90f0 completed March 8, 2026, 9:31 p.m.
Created at: March 1, 2026, 7:37 p.m.