Triple
T23534025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Marcello al Corso |
E576643
|
entity |
| Predicate | hasNumberOfSideChapels |
P16477
|
FINISHED |
| Object | several side chapels |
—
|
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: several side chapels | Statement: [San Marcello al Corso, hasNumberOfSideChapels, several side chapels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSideChapels Context triple: [San Marcello al Corso, hasNumberOfSideChapels, several side chapels]
-
A.
hasChapels
Indicates that one entity contains, includes, or is associated with one or more chapels.
-
B.
hasChapelCountApprox
chosen
Indicates an approximate number of chapels associated with an entity.
-
C.
hasTransept
Indicates that one architectural structure includes or features a transept as part of its design.
-
D.
hasNarthex
Indicates that one architectural structure (typically a church) includes or is equipped with a narthex area.
-
E.
eraOfOriginalChapel
Indicates the historical time period during which the original chapel associated with an entity was first constructed or established.
- 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_69e245f5a8848190a2ba42e271c6c31f |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ae14ae3c8190aa2714ea07a4658a |
completed | April 29, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:10 p.m.