Triple
T453949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blessed Sacrament |
E7190
|
entity |
| Predicate | reservedIn |
P1359
|
FINISHED |
| Object | tabernacle |
—
|
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: tabernacle | Statement: [Blessed Sacrament, reservedIn, tabernacle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reservedIn Context triple: [Blessed Sacrament, reservedIn, tabernacle]
-
A.
reservedFor
Indicates that something is set aside or allocated specifically for the use, benefit, or purpose of a particular entity or group.
-
B.
reserves
Indicates that an entity has arranged in advance to hold or secure something for future use or access.
-
C.
retained
Indicates that one entity keeps possession, control, or continued engagement of another entity over a period of time.
-
D.
held
Indicates that one entity physically grasped, carried, or kept another entity in its possession or control.
-
E.
protectedIn
chosen
Indicates that one entity is safeguarded, preserved, or kept safe within the context, environment, or jurisdiction 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef866e848190a5b700250ec56256 |
completed | Feb. 28, 2026, 1:37 p.m. |
| PD | Predicate disambiguation | batch_69a2ede4de008190b5a6c159e741522e |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.