Triple
T31433504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Ange-Gardien (Capitale-Nationale) |
E801858
|
entity |
| Predicate | isFrancophoneMajority |
P162956
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [L’Ange-Gardien (Capitale-Nationale), isFrancophoneMajority, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFrancophoneMajority Context triple: [L’Ange-Gardien (Capitale-Nationale), isFrancophoneMajority, true]
-
A.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
B.
isFrancophoneParty
Indicates that a political party primarily uses French or represents French-speaking communities.
-
C.
isInFrancophoneRegion
chosen
Indicates that an entity is located within a region where French is predominantly spoken or officially used.
-
D.
primaryFrenchDestination
Indicates that one entity is the main or most significant travel destination in France for another entity.
-
E.
isFrenchLanguageInstitution
Indicates that an institution primarily uses, promotes, or is officially associated with 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_69f348c475348190bf579ca858eec77c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 8:59 p.m.