Triple
T13766923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Louis |
E330771
|
entity |
| Predicate | nameBearerCulturalBackground |
P56388
|
FINISHED |
| Object | French-Canadian |
—
|
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-Canadian | Statement: [Jean-Louis, nameBearerCulturalBackground, French-Canadian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameBearerCulturalBackground Context triple: [Jean-Louis, nameBearerCulturalBackground, French-Canadian]
-
A.
languageOfNamesake
Indicates the language in which the namesake of an entity (such as a person, place, or object) is named or expressed.
-
B.
nameBearerType
Indicates the specific role or capacity in which an entity bears or carries a given name (e.g., as a person, place, organization, or other type of name bearer).
-
C.
cultureOfOrigin
chosen
Indicates the cultural background or tradition from which an entity originates or is derived.
-
D.
religiousNamesake
Indicates that one entity serves as the religiously significant figure, concept, or object after which the other entity is named.
-
E.
namesakeDescription
Indicates that the object provides a descriptive explanation of why or how the subject is considered a namesake of something or someone.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0227f2c48190983ccc9395e4e7a2 |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe97846c819093b00ea117b64e0d |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 10:10 p.m.