Triple

T1142329
Position Surface form Disambiguated ID Type / Status
Subject FIFA E23480 entity
Predicate headquartersLocation P62 FINISHED
Object Zürich, Switzerland 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, Switzerland | Statement: [FIFA, headquartersLocation, Zürich, Switzerland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zürich, Switzerland
Context triple: [FIFA, headquartersLocation, Zürich, Switzerland]
  • A. Bern, Switzerland
    Bern, Switzerland is the de facto capital of Switzerland, known for its well-preserved medieval old town, political institutions, and cultural heritage.
  • B. 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.
  • C. Lausanne, Switzerland
    Lausanne, Switzerland is a picturesque city on the shores of Lake Geneva known for its role as an Olympic capital and its vibrant cultural and academic life.
  • 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. Gland, Switzerland
    Gland, Switzerland is a small town on the shores of Lake Geneva that is best known as a global hub for environmental and conservation organizations.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc4d414881908fc636e8ccbc4c34 completed March 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae6ad879108190a28e2e07a1df35a0 completed March 9, 2026, 6:38 a.m.
Created at: March 1, 2026, 7:44 p.m.