Triple
T30483206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Procession of the Holy Blood |
E775642
|
entity |
| Predicate | hasCostumesFrom |
P203298
|
FINISHED |
| Object | biblical times |
—
|
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: biblical times | Statement: [Procession of the Holy Blood, hasCostumesFrom, biblical times]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCostumesFrom Context triple: [Procession of the Holy Blood, hasCostumesFrom, biblical times]
-
A.
hasCostumes
Indicates that one entity possesses, provides, or is associated with one or more costumes.
-
B.
hasCostumeBrand
Indicates that an entity’s costume is associated with or produced by a particular brand.
-
C.
haveDistinctCostume
Indicates that the entities each possess a costume that is different from the others’ costumes.
-
D.
stageCostume
Indicates that one entity is a costume specifically used or worn for a performance or stage production by another entity.
-
E.
colorAssociatedWithCostume
Indicates that a particular color is thematically or typically linked to a specific costume.
- 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_69f22497f91c8190afa7165bc900accd |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a014f7602988190b8f86cb431a9cf12 |
completed | May 11, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_6a014a70ea748190bd86fb9f218103ba |
completed | May 11, 2026, 3:18 a.m. |
| PDg | Predicate description generation | batch_6a014f751520819088cf1e697e0668ff |
completed | May 11, 2026, 3:39 a.m. |
Created at: April 29, 2026, 8:13 p.m.