Triple

T3264567
Position Surface form Disambiguated ID Type / Status
Subject Carouge E68492 entity
Predicate adjacentTo P224 FINISHED
Object Veyrier E54241 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: Veyrier | Statement: [Carouge, adjacentTo, Veyrier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Veyrier
Context triple: [Carouge, adjacentTo, Veyrier]
  • A. Veyrier chosen
    Veyrier is a municipality in southwestern Switzerland located just outside the city of Geneva, near the French border.
  • B. Veyrier-du-Lac
    Veyrier-du-Lac is a picturesque commune in southeastern France, nestled on the eastern shore of Lake Annecy at the foot of the Alps.
  • C. Gueugnon
    Gueugnon is a small commune in eastern France known historically for its steel industry and location in the Bourgogne-Franche-Comté region.
  • D. Bilhères
    Bilhères is a small mountain village in southwestern France, situated in the Ossau Valley of the Pyrenees.
  • E. 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.
  • 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_69ad8590444081909e8107a8aeef3a23 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafcb2da08190a7f4fefdfe6d0098 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e83a7a508190afd5342c79f3da9d completed March 12, 2026, 4:22 p.m.
Created at: March 8, 2026, 3:09 p.m.