Triple
T19070029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bona Dea |
E466766
|
entity |
| Predicate | cultCharacteristic |
P30241
|
FINISHED |
| Object | mystery cult aspects |
—
|
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: mystery cult aspects | Statement: [Bona Dea, cultCharacteristic, mystery cult aspects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cultCharacteristic Context triple: [Bona Dea, cultCharacteristic, mystery cult aspects]
-
A.
cultureCharacteristic
Indicates that a particular trait, practice, or feature is a defining characteristic of a given culture.
-
B.
popularCultureTrait
Indicates that an entity exhibits a characteristic, behavior, or element that is commonly recognized or influential within popular culture.
-
C.
traditionCharacteristic
chosen
Indicates that a particular quality, feature, or attribute is characteristic of, or typically associated with, a given tradition.
-
D.
regionalCharacteristic
Indicates that a particular feature, quality, or attribute is typical of, or distinctive to, a specific geographic region.
-
E.
themeCharacteristic
Indicates that a characteristic, quality, or property is attributed to or associated with a particular theme.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e19caa708190876a2cb06aa0c9cc |
completed | April 20, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69e4b99f602881909eeb9c780597e0e6 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:03 p.m.