Triple
T32868208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lady of the Abandoned Parish |
E840715
|
entity |
| Predicate | hasMarianImage |
P171437
|
FINISHED |
| Object | venerated image of Our Lady of the Abandoned |
—
|
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: venerated image of Our Lady of the Abandoned | Statement: [Our Lady of the Abandoned Parish, hasMarianImage, venerated image of Our Lady of the Abandoned]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarianImage Context triple: [Our Lady of the Abandoned Parish, hasMarianImage, venerated image of Our Lady of the Abandoned]
-
A.
hasMarianDedication
Indicates that something (typically a church, chapel, or shrine) is dedicated to or in honor of the Virgin Mary.
-
B.
hasSacredImage
chosen
Indicates that one entity possesses or is associated with an image regarded as sacred or religiously significant.
-
C.
hasImageRole
Indicates that an image is associated with an entity in a specific functional or contextual role (e.g., thumbnail, icon, illustration).
-
D.
hasImageFeature
Indicates that an entity is associated with a specific visual characteristic or attribute extracted from an image.
-
E.
containsImage
Indicates that one entity includes or embeds an image as part of its content or structure.
- 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_69f349436ee88190b72ee12d0f3f508e |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a00b03a50a88190bfb95cdcfc6142a2 |
completed | May 10, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_6a00afe55f248190b2cb4c7e62cc3ffc |
completed | May 10, 2026, 4:18 p.m. |
Created at: May 1, 2026, 1:17 a.m.