Triple

T1237481
Position Surface form Disambiguated ID Type / Status
Subject Robert Estienne E26579 entity
Predicate movedTo P195 FINISHED
Object Geneva E414 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: Geneva | Statement: [Robert Estienne, movedTo, Geneva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geneva
Context triple: [Robert Estienne, movedTo, Geneva]
  • A. Geneva chosen
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • B. 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.
  • C. 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.
  • D. Zurich
    Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
  • E. Geneva metropolitan area
    The Geneva metropolitan area is the cross-border urban region centered on the city of Geneva, spanning parts of Switzerland and France and functioning as a major international, financial, and diplomatic hub.
  • 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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf3f07c08190a402e8341c1f38cc completed March 1, 2026, 10:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd4620c7c81909e30a2dfd55602fb completed March 8, 2026, 1:44 a.m.
Created at: March 1, 2026, 7:47 p.m.