Triple
T31347705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 5e Régiment d’artillerie légère du Canada |
E799493
|
entity |
| Predicate | isFrancophoneUnitOf |
P91232
|
FINISHED |
| Object | Canadian Army |
—
|
NE NERFINISHED |
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: Canadian Army | Statement: [5e Régiment d’artillerie légère du Canada, isFrancophoneUnitOf, Canadian Army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFrancophoneUnitOf Context triple: [5e Régiment d’artillerie légère du Canada, isFrancophoneUnitOf, Canadian Army]
-
A.
isFrancophoneCounterpartOf
chosen
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
B.
isInFrancophoneRegion
Indicates that an entity is located within a region where French is predominantly spoken or officially used.
-
C.
isFrancophoneParty
Indicates that a political party primarily uses French or represents French-speaking communities.
-
D.
isFrenchLanguageInstitution
Indicates that an institution primarily uses, promotes, or is officially associated with the French language.
-
E.
containsFrenchPhrases
Indicates that the subject includes one or more phrases expressed in the French 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_69f224e51614819083141459a080e97c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f19a79c81909647d8eef6706e44 |
completed | May 3, 2026, 1:04 a.m. |
| PD | Predicate disambiguation | batch_69f69d1d25e88190a7f57d323574da90 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:17 p.m.