Triple

T42234
Position Surface form Disambiguated ID Type / Status
Subject Europe E833 entity
Predicate hasMajorCity P316 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: [Europe, hasMajorCity, Geneva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geneva
Context triple: [Europe, hasMajorCity, 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. canton of Geneva
    The canton of Geneva is the westernmost Swiss canton, encompassing the city of Geneva and serving as a major international, diplomatic, and financial hub.
  • E. Strasbourg
    Strasbourg is a major French city on the Rhine known for hosting key European institutions, including the European Parliament and the Council of Europe.
  • 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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24ae236548190bd225d125f23e6c7 completed Feb. 28, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a29e420aa0819085d796612c24bcac completed Feb. 28, 2026, 7:50 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.