Triple
T1649770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Member of the Order of Canada |
E35663
|
entity |
| Predicate | FrenchTitle |
P7000
|
FINISHED |
| Object | Membre de l’Ordre du Canada |
—
|
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: Membre de l’Ordre du Canada | Statement: [Member of the Order of Canada, FrenchTitle, Membre de l’Ordre du Canada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FrenchTitle Context triple: [Member of the Order of Canada, FrenchTitle, Membre de l’Ordre du Canada]
-
A.
equivalentTitleInFrench
chosen
Indicates that one entity’s title is the equivalent or corresponding title of another entity, specifically expressed in French.
-
B.
nameInFrench
Indicates that an entity is known or referred to by a specific name expressed in the French language.
-
C.
FrenchCommander
Indicates that an entity serves as a military commander associated with France.
-
D.
FrenchObjective
Indicates that an entity serves as the goal, target, or object of an action or relation specifically within a French linguistic or contextual framework.
-
E.
europeanTitle
Indicates that an entity holds or is associated with a formal title recognized within a European country or European nobility system.
- 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaa0fbe984819084f8daee81ca9b67 |
completed | March 6, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69a907ce4dd881909168a1e99505d4ec |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:29 p.m.