Triple
T18926586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monte Lussari |
E462988
|
entity |
| Predicate | hasChapelOriginLegend |
P133820
|
FINISHED |
| Object | discovery of a statue of the Virgin Mary by shepherds |
—
|
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: discovery of a statue of the Virgin Mary by shepherds | Statement: [Monte Lussari, hasChapelOriginLegend, discovery of a statue of the Virgin Mary by shepherds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapelOriginLegend Context triple: [Monte Lussari, hasChapelOriginLegend, discovery of a statue of the Virgin Mary by shepherds]
-
A.
hasChapelLocation
Indicates that one entity serves as the physical location or site where a chapel associated with another entity is situated.
-
B.
hasChapelDecoration
Indicates that a chapel possesses or features a particular decorative element or ornamentation.
-
C.
hasChapels
Indicates that one entity contains, includes, or is associated with one or more chapels.
-
D.
hasChapelStyle
Indicates that a chapel possesses or is characterized by a particular architectural or stylistic design.
-
E.
hasChapelUse
Indicates that something is used, designated, or functions as a chapel or for chapel-related purposes.
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c9bc36588190ae9cc3b8abf8afd4 |
completed | April 20, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 11:59 a.m.