Triple

T498231
Position Surface form Disambiguated ID Type / Status
Subject Additional Protocol III E10342 entity
Predicate adoptedAt P3076 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: [Additional Protocol III, adoptedAt, Geneva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geneva
Context triple: [Additional Protocol III, adoptedAt, 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. Zurich
    Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
  • C. 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.
  • D. Neuchâtel
    Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
  • E. 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.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1183e988190bce70932a9678134 completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4b5ce2ff88190ac180c4df9604028 completed March 1, 2026, 9:55 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.