Triple

T4343994
Position Surface form Disambiguated ID Type / Status
Subject Markets Committee E97854 entity
Predicate location P40 FINISHED
Object Basel, Switzerland E22322 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: Basel, Switzerland | Statement: [Markets Committee, location, Basel, Switzerland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Basel, Switzerland
Context triple: [Markets Committee, location, Basel, 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. 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.
  • C. Basel-Stadt chosen
    Basel-Stadt is a small, urban Swiss canton centered on the city of Basel, a major cultural and economic hub in northwestern Switzerland.
  • 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. Zurich
    Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
  • 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_69b34548402c819085ab68b27c235a87 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3518aa5cc8190b50f47b1070715fe completed March 12, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67ac56548190a2d52b055cb48e8e completed March 21, 2026, 9:41 a.m.
Created at: March 12, 2026, 11:14 p.m.