Triple
T36006576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chapel of the Crucifix |
E1041286
|
entity |
| Predicate | hasSubjectMatterInArt |
P110363
|
FINISHED |
| Object | Crucifixion of Christ |
—
|
NE NERFINISHED |
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: Crucifixion of Christ | Statement: [Chapel of the Crucifix, hasSubjectMatterInArt, Crucifixion of Christ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectMatterInArt Context triple: [Chapel of the Crucifix, hasSubjectMatterInArt, Crucifixion of Christ]
-
A.
hasArtSubjects
chosen
Indicates that an entity is associated with one or more subjects or themes within the domain of art.
-
B.
hasArtisticDiscipline
Indicates that one entity practices, specializes in, or is associated with a particular artistic discipline or field.
-
C.
hasArtisticRelevance
Indicates that something bears meaningful artistic significance or contributes in a relevant way to artistic value, interpretation, or context.
-
D.
hasArtisticFocus
Indicates that an entity’s primary artistic attention, theme, or specialization is directed toward a particular subject, style, or medium.
-
E.
hasArtProgram
Indicates that an entity offers or participates in an art-related educational or creative program.
- 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_69f76e2a02208190aedd1f9025a8b300 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a0004582bb08190b8d0b88251e8d333 |
completed | May 10, 2026, 4:06 a.m. |
| PD | Predicate disambiguation | batch_6a0003e3e5588190933beea5fb28f150 |
completed | May 10, 2026, 4:04 a.m. |
Created at: May 3, 2026, 4:07 p.m.