Triple
T35134658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of Santa Maria Immacolata a Via Veneto |
E1014535
|
entity |
| Predicate | numberOfBurialsApprox |
P148531
|
FINISHED |
| Object | thousands of Capuchin friars |
—
|
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: thousands of Capuchin friars | Statement: [Church of Santa Maria Immacolata a Via Veneto, numberOfBurialsApprox, thousands of Capuchin friars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBurialsApprox Context triple: [Church of Santa Maria Immacolata a Via Veneto, numberOfBurialsApprox, thousands of Capuchin friars]
-
A.
numberOfBurials
Indicates the total count of burial events associated with a given entity.
-
B.
numberOfGravesApproximate
chosen
Indicates that the stated count of graves is an estimated or approximate number rather than an exact figure.
-
C.
numberOfInterred
Indicates the total count of individuals who are buried or interred at a given site or within a specified context.
-
D.
cemeteryBurialsSince
Indicates the number of burials that have occurred in a cemetery from a specified point in time onward.
-
E.
hasBurialsFrom
Indicates that a location or site contains burials originating from a specified time period, culture, or source.
- 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_69f76dd9c1848190af70d4882a2c1ad7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:02 p.m.