Triple
T10259351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indulgences in the Catholic Church |
E240553
|
entity |
| Predicate | effectOfPartial |
P58916
|
FINISHED |
| Object | partial remission of temporal punishment |
—
|
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: partial remission of temporal punishment | Statement: [Indulgences in the Catholic Church, effectOfPartial, partial remission of temporal punishment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOfPartial Context triple: [Indulgences in the Catholic Church, effectOfPartial, partial remission of temporal punishment]
-
A.
isPartially
Indicates that one entity is included within another to some extent, but not completely or fully.
-
B.
effectOnOthers
chosen
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
C.
partiallyPreserved
Indicates that the referenced entity or object is only incompletely intact, with some parts missing, damaged, or lost while others remain.
-
D.
effectOnUnion
Indicates the impact or influence that something has on a union as a whole.
-
E.
partiallyPreservedThrough
Indicates that something is not fully intact but has been maintained or conserved to some extent by or via another entity or medium.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b5853081909cd0397e08a0f44d |
completed | April 7, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69d4d1edae6881909a65201b8e51ea0a |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:32 a.m.