Triple
T6399002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deposition of the Robe of the Mother of God |
E144011
|
entity |
| Predicate | hasFeastCategory |
P9865
|
FINISHED |
| Object | Marian devotion |
—
|
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: Marian devotion | Statement: [Deposition of the Robe of the Mother of God, hasFeastCategory, Marian devotion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFeastCategory Context triple: [Deposition of the Robe of the Mother of God, hasFeastCategory, Marian devotion]
-
A.
hasAssociatedFeast
Indicates that something (such as a person, event, or entity) is linked to a specific feast or celebratory religious observance.
-
B.
feastType
chosen
Indicates the specific kind or category of feast associated with an event or occasion.
-
C.
hasFeastOrCommemoration
Indicates that a particular day, event, or context includes an associated religious feast, liturgical celebration, or commemorative observance.
-
D.
hasObligationOfFestiveMeal
Indicates that an entity is required to participate in or provide a festive meal as a formal obligation.
-
E.
hasMealType
Indicates that an entity is associated with a specific category or type of meal (such as breakfast, lunch, or dinner).
- 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_69c008dc56fc81908d43ffcc11d73bdd |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06897ebc48190842d48cce469eba5 |
completed | March 22, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69c060f25c088190b433f78553ff1d84 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:35 p.m.