Triple

T19962173
Position Surface form Disambiguated ID Type / Status
Subject ANOC E479841 entity
Predicate headquartersLocation P62 FINISHED
Object Lausanne, Switzerland NE NERFINISHED

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: Lausanne, Switzerland | Statement: [ANOC, headquartersLocation, Lausanne, Switzerland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lausanne, Switzerland
Context triple: [ANOC, headquartersLocation, Lausanne, Switzerland]
  • A. 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.
  • B. Lucerne, Switzerland
    Lucerne, Switzerland is a picturesque city in central Switzerland known for its preserved medieval architecture, lakeside setting on Lake Lucerne, and surrounding mountain scenery.
  • C. Lausanne chosen
    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. Bern, Switzerland
    Bern, Switzerland is the de facto capital of Switzerland, known for its well-preserved medieval old town, political institutions, and cultural heritage.
  • E. Geneva
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e523c19881909f9197037200dde6 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65af51b4c81909ba156a489cbc551 completed April 20, 2026, 4:57 p.m.
Created at: April 10, 2026, 1:54 p.m.