Triple

T5521717
Position Surface form Disambiguated ID Type / Status
Subject Arezzo E144823 entity
Predicate twinTown P1072 FINISHED
Object Saint-Priest E364907 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: Saint-Priest | Statement: [Arezzo, twinTown, Saint-Priest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saint-Priest
Context triple: [Arezzo, twinTown, Saint-Priest]
  • A. Saint-Priest chosen
    Saint-Priest is a suburban commune in eastern France that forms part of the metropolitan area of Lyon.
  • B. Firminy
    Firminy is a commune in central France known for its notable modernist architecture, including works by Le Corbusier such as the Maison de la Culture.
  • C. Meyzieu
    Meyzieu is a suburban commune in eastern France, located near Lyon and known for its residential character and proximity to major transport links.
  • D. Vaulx-en-Velin
    Vaulx-en-Velin is a suburban commune in eastern France located just northeast of Lyon, known for its large housing estates and diverse population.
  • E. Vanves
    Vanves is a suburban commune in the southwestern outskirts of Paris, France, known for its dense residential character and proximity to the capital.
  • 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_69c008f873a481909b4d9f7e2db3c37d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f7227a8819080c9f074afe0eaac completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c99ba1bbdc81909269ac0a97caa91d completed March 29, 2026, 9:37 p.m.
Created at: March 22, 2026, 3:33 p.m.