Triple

T22000314
Position Surface form Disambiguated ID Type / Status
Subject Vision Montréal E543305 entity
Predicate operatedLanguageEnvironment P19095 FINISHED
Object French and English political context in Montreal LITERAL 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: French and English political context in Montreal | Statement: [Vision Montréal, operatedLanguageEnvironment, French and English political context in Montreal]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: operatedLanguageEnvironment
Context triple: [Vision Montréal, operatedLanguageEnvironment, French and English political context in Montreal]
  • A. languageOfOperation
    Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
  • B. languageOfEnvironment chosen
    Indicates the language predominantly used or present in a given environment or context.
  • C. languageOfOperator
    Indicates that a particular language is used by, or associated with, a given operator in performing its functions or services.
  • D. usesLanguageRuntime
    Indicates that an entity operates using, depends on, or is executed within a specific language runtime environment.
  • E. tertiaryLanguageOfOperation
    Indicates that an entity uses a specified language as its third most prominent or prioritized language of operation.
  • F. None of above.

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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127699a7881908a80b6e9e33fcc0b completed April 28, 2026, 9:32 p.m.
PD Predicate disambiguation batch_69e6f62dc9d88190ae387f145f9528de completed April 21, 2026, 3:59 a.m.
Created at: April 16, 2026, 8:20 p.m.