Triple
T24572422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of Santa Prassede |
E607996
|
entity |
| Predicate | materialOfMosaics |
P63728
|
FINISHED |
| Object | glass tesserae |
—
|
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: glass tesserae | Statement: [Church of Santa Prassede, materialOfMosaics, glass tesserae]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialOfMosaics Context triple: [Church of Santa Prassede, materialOfMosaics, glass tesserae]
-
A.
mosaicMaterial
chosen
Indicates that something is made of, or incorporates, a specified material in its mosaic construction.
-
B.
materialDepicted
Indicates that a work or representation visually portrays or includes a particular material as part of its subject.
-
C.
mosaicCreator
Indicates that an entity is the artist or maker responsible for creating a particular mosaic.
-
D.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
E.
streetMaterial
Indicates the material composition from which a street or road surface is made.
- 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_69e2c4cdab6c8190aae6e5d3de55c95e |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a9269360819090c44f4483c3533c |
completed | April 30, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:28 a.m.