Triple
T6367677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basilica of Sant'Apollinare Nuovo |
E143266
|
entity |
| Predicate | hasAisleCount |
P31470
|
FINISHED |
| Object | two side aisles |
—
|
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: two side aisles | Statement: [Basilica of Sant'Apollinare Nuovo, hasAisleCount, two side aisles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAisleCount Context triple: [Basilica of Sant'Apollinare Nuovo, hasAisleCount, two side aisles]
-
A.
hasAisles
Indicates that a location or structure contains one or more aisles as part of its internal layout or organization.
-
B.
numberOfAisles
chosen
Indicates the total count of aisles associated with or contained within a given entity.
-
C.
numberOfBays
Indicates the count of distinct bays associated with or contained within a given entity.
-
D.
numberOfFloorsInAnchorStores
Indicates the relationship specifying how many floors are contained within each anchor store.
-
E.
numberOfHalls
Indicates the quantity of halls associated with a given entity or location.
- 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_69c008d8c61081908bcaf61510d881ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c068251ae48190af8201d5f9ad35b6 |
completed | March 22, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69c060ee055081908c79a1d151bd74cd |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:32 p.m.