Triple
T1238183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sant’Anna |
E26594
|
entity |
| Predicate | hasDevotionType |
P21326
|
FINISHED |
| Object | Marian-related 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-related devotion | Statement: [Sant’Anna, hasDevotionType, Marian-related devotion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDevotionType Context triple: [Sant’Anna, hasDevotionType, Marian-related devotion]
-
A.
associatedDevotion
chosen
Indicates a relationship where one entity is linked to or characterized by a particular devotion, dedication, or religious/spiritual practice connected to another entity.
-
B.
hasClergyType
Indicates the specific category or role of clergy associated with an entity.
-
C.
hasDeity
Indicates that one entity recognizes, worships, or is associated with another entity as its deity or divine figure.
-
D.
hasDeityGroup
Indicates a relationship where an entity is associated with, or belongs to, a particular group or pantheon of deities.
-
E.
typeOfDeity
Indicates that one entity is classified as a specific kind or category of deity in relation to another.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf406b988190a12aa26bbcb88d6a |
completed | March 1, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69a4bb67d52c8190815d6356b79d6ed5 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.