Triple
T15105337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basilica of Santa Maria in Domnica |
E360773
|
entity |
| Predicate | hasMosaicSubject |
P117340
|
FINISHED |
| Object | Virgin Mary enthroned with Child |
—
|
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: Virgin Mary enthroned with Child | Statement: [Basilica of Santa Maria in Domnica, hasMosaicSubject, Virgin Mary enthroned with Child]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMosaicSubject Context triple: [Basilica of Santa Maria in Domnica, hasMosaicSubject, Virgin Mary enthroned with Child]
-
A.
hasMosaic
Indicates that one entity possesses, contains, or is decorated with a mosaic.
-
B.
hasMosaicsBy
Indicates that something contains or features mosaics that were created by a specified agent or creator.
-
C.
hasCollectionSubject
Indicates that a collection is about or thematically centered on a particular subject.
-
D.
hasMetaSubject
Indicates that an entity is associated with a subject at a meta-level, such as the topic, theme, or aboutness of the entity rather than its direct content or participants.
-
E.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00588f35481909674f161bf0f3918 |
completed | April 15, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69deb96c1d9c81909351558ed97bc5b7 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:05 a.m.