Triple
T35349816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | École secondaire Saint-Jean-Eudes |
E1020846
|
entity |
| Predicate | operatesOnLanguage |
P78017
|
FINISHED |
| Object | French |
—
|
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 | Statement: [École secondaire Saint-Jean-Eudes, operatesOnLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesOnLanguage Context triple: [École secondaire Saint-Jean-Eudes, operatesOnLanguage, French]
-
A.
languageOfOperation
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
-
B.
isSupportedByLanguage
Indicates that something (such as a feature, format, or construct) is compatible with and can be handled or recognized by a particular language.
-
C.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
D.
usesLanguageSupport
Indicates that one entity makes use of language-related assistance, features, or services provided by another entity.
-
E.
hasPrimaryLanguageOfOperations
chosen
Indicates that an entity conducts its main activities or operations primarily using a specified language.
- 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_69f76decd95c8190ae428f6a19d535de |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a01378bf05c8190af9f5e06a2810c7d |
completed | May 11, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_6a0137277c6c8190bcec341f2a0757c4 |
completed | May 11, 2026, 1:55 a.m. |
Created at: May 3, 2026, 4:03 p.m.