Triple
T35260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virgin Mary |
E698
|
entity |
| Predicate | virtueAssociated |
P662
|
FINISHED |
| Object | purity |
—
|
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: purity | Statement: [Virgin Mary, virtueAssociated, purity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: virtueAssociated Context triple: [Virgin Mary, virtueAssociated, purity]
-
A.
notablyAssociatedWith
Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
-
B.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
C.
promotes
Indicates that one entity actively supports, advances, or encourages the growth, adoption, or success of another entity or outcome.
-
D.
organizationAssociatedWith
Indicates that there is a formal or recognized connection or affiliation between an organization and another entity.
-
E.
associatedWithDiscipline
Indicates that an entity has a relevant connection or involvement with a particular academic, professional, or thematic discipline.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24989c3308190af59dfae37cfc32f |
completed | Feb. 28, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69a24873e97c8190b9e4279e43b6de14 |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.