Triple

T680020
Position Surface form Disambiguated ID Type / Status
Subject Prévessin-Moëns E13160 entity
Predicate partOf P40 FINISHED
Object Pays de Gex E110898 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: Pays de Gex | Statement: [Prévessin-Moëns, partOf, Pays de Gex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pays de Gex
Context triple: [Prévessin-Moëns, partOf, Pays de Gex]
  • A. Pays de Gex chosen
    Pays de Gex is a region in eastern France near the Swiss border, known for its proximity to Geneva and the Jura Mountains.
  • B. Lancy
    Lancy is a suburban municipality in western Switzerland that forms part of the urban area of Geneva.
  • C. Montgenèvre
    Montgenèvre is a French Alpine ski resort village in the Hautes-Alpes department, known for its high-altitude slopes and location near the Italian border.
  • D. Mulhouse
    Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
  • E. Besançon
    Besançon is a historic city in eastern France, known for its well-preserved Vauban fortifications, rich cultural heritage, and role as a regional administrative and educational center.
  • 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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a04f4efc819082767a7517fa760a completed March 1, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69aca2caba8c81908ef693677acbd4cc completed March 7, 2026, 10:12 p.m.
Created at: March 1, 2026, 7:36 p.m.