Triple
T11007983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Candlemas |
E260169
|
entity |
| Predicate | hasCulturalCustom |
P11746
|
FINISHED |
| Object | eating crêpes in France |
—
|
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: eating crêpes in France | Statement: [Candlemas, hasCulturalCustom, eating crêpes in France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCulturalCustom Context triple: [Candlemas, hasCulturalCustom, eating crêpes in France]
-
A.
hasCulturalFeature
Indicates that an entity possesses, includes, or is characterized by a particular cultural element, attribute, or landmark.
-
B.
hasCulturalConcept
Indicates that an entity embodies, includes, or is associated with a particular cultural idea, value, practice, or construct.
-
C.
hasCulturalExpression
chosen
Indicates that an entity embodies, manifests, or is associated with a particular cultural form, practice, or expression.
-
D.
hasCulturalIcon
Indicates that an entity is associated with or possesses a person, symbol, or object widely recognized as a significant representation of a particular culture.
-
E.
hasCulturalFunction
Indicates that something serves a particular role, purpose, or function within a culture or cultural context.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79757bdcc8190900b267826eece21 |
completed | April 9, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69d72e96be6c8190a46c69f61b2d8cd4 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:25 p.m.