Triple
T34406583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wukro Chirkos Church |
E883129
|
entity |
| Predicate | hasRitualObjects |
P7123
|
FINISHED |
| Object | tabot (altar tablet) |
—
|
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: tabot (altar tablet) | Statement: [Wukro Chirkos Church, hasRitualObjects, tabot (altar tablet)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRitualObjects Context triple: [Wukro Chirkos Church, hasRitualObjects, tabot (altar tablet)]
-
A.
hasRitualObject
chosen
Indicates that an entity possesses, uses, or is associated with an object specifically employed in a ritual or ceremonial context.
-
B.
hasRitualObjectMaterial
Indicates that a ritual object is made from, composed of, or primarily constructed using a specified material.
-
C.
hasRitualElements
Indicates that one entity incorporates, contains, or is characterized by ritualistic components, practices, or features associated with formalized ceremonies or rites.
-
D.
hasRitual
Indicates that an entity performs, observes, or is associated with a specific ritual or ceremonial practice.
-
E.
hasRituals
Indicates that one entity performs, observes, or is associated with specific rituals in relation to another entity or context.
- 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_69f349c1f2208190a09a489bb8b2719d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: May 1, 2026, 1:59 a.m.