Triple
T84595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holy Eucharist |
E1701
|
entity |
| Predicate | viewVariesAmong |
P3474
|
FINISHED |
| Object | Christian denominations |
—
|
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: Christian denominations | Statement: [Holy Eucharist, viewVariesAmong, Christian denominations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewVariesAmong Context triple: [Holy Eucharist, viewVariesAmong, Christian denominations]
-
A.
locationVariesWith
Indicates that the location of one entity changes in dependence on, or as a function of, changes in another entity.
-
B.
parentVariety
Indicates that one variety is the direct parent or source variety from which another variety is derived or developed.
-
C.
viewsGraceAs
Indicates that one entity regards or perceives Grace in a particular way or role.
-
D.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
E.
visitorCount
Indicates the number of visitors associated with a particular entity, context, or time period.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f4e73c081908d2da146226ef05e |
completed | Feb. 28, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69a24eb469548190b38c24e81f36c838 |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a24f4b4658819087902414959161fb |
completed | Feb. 28, 2026, 2:13 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.