Triple
T34770934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | maqdas |
E1002358
|
entity |
| Predicate | hasLiturgicalFurnishing |
P197308
|
FINISHED |
| Object | altar canopy (where present) |
—
|
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: altar canopy (where present) | Statement: [maqdas, hasLiturgicalFurnishing, altar canopy (where present)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiturgicalFurnishing Context triple: [maqdas, hasLiturgicalFurnishing, altar canopy (where present)]
-
A.
hasLiturgicalSymbol
Indicates that one entity serves as a liturgical symbol or emblem associated with another entity within a religious or worship context.
-
B.
hasAltarPieceFrom
Indicates that an altar piece originates from, or is sourced from, a particular place, creator, or context.
-
C.
aimsForLiturgicalUse
Indicates that something is intended or designed specifically for use in liturgical or formal religious worship contexts.
-
D.
isInUseForWorship
Indicates that something is currently being used for religious or worship-related activities.
-
E.
hasLiturgicalSpace
Indicates that one entity provides or contains a designated space used for liturgical or religious worship activities in relation to another entity.
- F. None of above. chosen
Provenance (4 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_69f76db20dac8190b1e8d0ca4dc1d59f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
| PDg | Predicate description generation | batch_69fe86c98d688190a99d5dcb14e2dc95 |
completed | May 9, 2026, 12:58 a.m. |
Created at: May 3, 2026, 3:59 p.m.