Triple
T33054063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yule log |
E845802
|
entity |
| Predicate | culturalVariant |
P34737
|
FINISHED |
| Object | Bûche de Noël in French cuisine |
—
|
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: Bûche de Noël in French cuisine | Statement: [Yule log, culturalVariant, Bûche de Noël in French cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: culturalVariant Context triple: [Yule log, culturalVariant, Bûche de Noël in French cuisine]
-
A.
culturalVariation
Indicates that there are differences in practices, beliefs, or expressions between cultures or within a culture across groups, contexts, or time.
-
B.
linguisticVariant
chosen
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
C.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
D.
culturalIdentifier
Indicates that one entity serves as a marker, label, or attribute that identifies or characterizes the cultural affiliation, background, or context of another entity.
-
E.
usedCulture
Indicates that one entity employed, applied, or drew upon the cultural practices, norms, or artifacts associated with another 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_69f3495242e48190996a2cb2beab5455 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7b2f3a104819098ddd8909eaf596c |
completed | May 3, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f7b1b8a9fc8190a1279e67a2d12707 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 1, 2026, 1:24 a.m.