Triple
T15435010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assumption Day pilgrimage |
E369735
|
entity |
| Predicate | feastClassification |
P9865
|
FINISHED |
| Object | Marian feast |
—
|
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 feast | Statement: [Assumption Day pilgrimage, feastClassification, Marian feast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: feastClassification Context triple: [Assumption Day pilgrimage, feastClassification, Marian feast]
-
A.
feastType
chosen
Indicates the specific kind or category of feast associated with an event or occasion.
-
B.
feastTraditionalName
Indicates the traditional or customary name by which a particular feast or celebration is known.
-
C.
feast
Indicates that an entity participates in or hosts a large, elaborate meal or celebration involving abundant food and communal dining.
-
D.
feastFollows
Indicates that a feast or celebratory meal occurs after and as a consequence of a preceding event or action.
-
E.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03edb3ec481908b26164d4470c9bc |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded27f45548190a6d2b1b85cb47444 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:21 a.m.