Triple

T3811049
Position Surface form Disambiguated ID Type / Status
Subject Annemasse E93133 entity
Predicate hasBorderWith P224 FINISHED
Object Étrembières E308509 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: Étrembières | Statement: [Annemasse, hasBorderWith, Étrembières]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Étrembières
Context triple: [Annemasse, hasBorderWith, Étrembières]
  • A. Étrembières chosen
    Étrembières is a commune in southeastern France’s Haute-Savoie department, located near Geneva along the French-Swiss border.
  • B. Fléron
    Fléron is a municipality in eastern Belgium located in the Walloon region’s Province of Liège.
  • C. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • D. Éveux
    Éveux is a small commune in eastern France’s Rhône department, known for hosting Le Corbusier’s modernist monastery, the Couvent Sainte-Marie de La Tourette.
  • E. Chamrousse
    Chamrousse is a French alpine ski resort and mountain commune in the Alps, known for its winter sports facilities and scenic high-altitude landscapes.
  • 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee80faaa88190b05f8aec8aa5c44d completed March 9, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb373ce4819082e2d6d6c204c392 completed March 14, 2026, 6:07 a.m.
Created at: March 9, 2026, 3:16 p.m.