Triple
T5793642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Vincenzo, Modena |
E128454
|
entity |
| Predicate | hasAltarpieces |
P61874
|
FINISHED |
| Object | Baroque altarpieces |
—
|
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: Baroque altarpieces | Statement: [San Vincenzo, Modena, hasAltarpieces, Baroque altarpieces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAltarpieces Context triple: [San Vincenzo, Modena, hasAltarpieces, Baroque altarpieces]
-
A.
hasAltarpiecesInStyle
chosen
Indicates that an entity possesses or features altarpieces that are created or designed in a specified artistic style.
-
B.
hasFrescoes
Indicates that something contains or is adorned with fresco paintings as part of its structure or decoration.
-
C.
hasIconostasis
Indicates that a place of worship contains or is equipped with an iconostasis, a partition or screen bearing icons that separates different liturgical spaces.
-
D.
hasAltar
Indicates that one entity possesses, contains, or includes an altar as part of its features or components.
-
E.
hasSacristy
Indicates that a religious building includes or is associated with a sacristy (a room where sacred vessels, vestments, and liturgical items are kept and prepared).
- 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b1304588190b59a18fb7b70a60f |
completed | March 22, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69c021d477008190946113f9859eeb90 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:51 p.m.