Triple
T2819249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Divine Mercy Sunday |
E54366
|
entity |
| Predicate | hasSpecialIndulgence |
P43510
|
FINISHED |
| Object | plenary indulgence under usual conditions |
—
|
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: plenary indulgence under usual conditions | Statement: [Divine Mercy Sunday, hasSpecialIndulgence, plenary indulgence under usual conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpecialIndulgence Context triple: [Divine Mercy Sunday, hasSpecialIndulgence, plenary indulgence under usual conditions]
-
A.
hasSpecials
Indicates that an entity offers or is associated with special deals, promotions, or limited-time offers.
-
B.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
C.
hasSpecialMeal
Indicates that an entity provides, is assigned, or is associated with a designated special meal option.
-
D.
hasSpecialRules
Indicates that certain entities are governed by additional or exceptional rules that differ from the standard ones.
-
E.
hasSpecialtyFood
Indicates that an entity offers, serves, or is associated with a particular type of specialty food.
- 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abdf15b7288190a03d1193cc0544a6 |
completed | March 7, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69abdd08f2f481908c3da8a9c7a00552 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdf13d2b8819097b8edaaea90dbe2 |
completed | March 7, 2026, 8:17 a.m. |
Created at: March 6, 2026, 9:59 p.m.