Triple
T23774376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Matthew by Michelangelo |
E587627
|
entity |
| Predicate | significantPlaceAssociatedWithWork |
P57645
|
FINISHED |
| Object | Florence |
—
|
NE NERFINISHED |
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: Florence | Statement: [St. Matthew by Michelangelo, significantPlaceAssociatedWithWork, Florence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significantPlaceAssociatedWithWork Context triple: [St. Matthew by Michelangelo, significantPlaceAssociatedWithWork, Florence]
-
A.
notablePlaceOfWork
Indicates that there is a notable or significant place where the entity has worked or been employed.
-
B.
heritageDesignationRelatedToWork
Indicates that a heritage designation is connected or applicable to a specific work (such as an artwork, building, or cultural object).
-
C.
notableBuildingAssociated
chosen
Indicates a relationship where a notable or significant building is associated with, connected to, or relevant to a given entity.
-
D.
significantPlaceType
Indicates the type or category of place that holds particular significance in relation to the subject.
-
E.
significantMonument
Indicates that something is a monument of notable historical, cultural, or symbolic importance.
- 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_69e2490d245881909028226a1393d624 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c468fb948190baa66a4353f0ca71 |
completed | April 29, 2026, 8:42 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:16 p.m.