Triple
T6768388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Officer of the National Order of Quebec |
E154980
|
entity |
| Predicate | hasLanguageOfInsignia |
P5036
|
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: [Grand Officer of the National Order of Quebec, hasLanguageOfInsignia, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfInsignia Context triple: [Grand Officer of the National Order of Quebec, hasLanguageOfInsignia, French]
-
A.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
B.
emblemLanguage
chosen
Indicates that an emblem (such as a symbol or logo) is associated with or presented in a particular language.
-
C.
hasNotableLanguageWithOfficialStatusIn
Indicates that a language holds an officially recognized and notable status within a specified jurisdiction or region.
-
D.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
-
E.
languageOfFounders
Indicates the language or languages spoken or used by the founders of an entity.
- 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_69c68812ef7c819099369f51febb725c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d231b79c81908a4f7fa8f253706d |
completed | March 27, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:12 p.m.