Triple

T929664
Position Surface form Disambiguated ID Type / Status
Subject Radio Télévision Suisse E20061 entity
Predicate hasOffice P1268 FINISHED
Object Lausanne E74605 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: Lausanne | Statement: [Radio Télévision Suisse, hasOffice, Lausanne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lausanne
Context triple: [Radio Télévision Suisse, hasOffice, Lausanne]
  • A. 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.
  • B. Neuchâtel
    Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
  • C. Geneva
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • D. Nyon
    Nyon is a Swiss town on the shores of Lake Geneva that serves as the administrative home of several major sports organizations, including UEFA.
  • E. Montreux
    Montreux is a picturesque resort town in southwestern Switzerland, renowned for its lakeside promenade, mild microclimate, and the annual Montreux Jazz Festival.
  • 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_69a493af3dc48190adb7263e6e445ea1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b349b3d0819090c58b4fb60c6a1b completed March 1, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1de5dc6e88190beda5545a2e2f84c completed March 11, 2026, 9:27 p.m.
Created at: March 1, 2026, 7:40 p.m.