Triple
T16127090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pontmain |
E391298
|
entity |
| Predicate | hasReligiousArt |
P110363
|
FINISHED |
| Object | Marian iconography |
—
|
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: Marian iconography | Statement: [Pontmain, hasReligiousArt, Marian iconography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousArt Context triple: [Pontmain, hasReligiousArt, Marian iconography]
-
A.
hasArtSubjects
chosen
Indicates that an entity is associated with one or more subjects or themes within the domain of art.
-
B.
hasArtFacilities
Indicates that an entity provides or is equipped with facilities or resources dedicated to art-related activities.
-
C.
hasReligiousTheme
Indicates that something (such as a work, event, or object) centrally involves or expresses religious ideas, symbols, practices, or narratives.
-
D.
hasArtOrMemorial
Indicates that one entity possesses, contains, or is associated with a work of art or a memorial related to another entity.
-
E.
hasReligiousSee
Indicates that one entity serves as the ecclesiastical or religious jurisdiction/seat (see) of 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20205bed48190a6930439738da191 |
completed | April 17, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5 a.m.