Triple
T28466495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palacio Barolo |
E720305
|
entity |
| Predicate | symbolicStoreysCount |
P166483
|
FINISHED |
| Object | related to the 100 cantos of the Divine Comedy |
—
|
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: related to the 100 cantos of the Divine Comedy | Statement: [Palacio Barolo, symbolicStoreysCount, related to the 100 cantos of the Divine Comedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolicStoreysCount Context triple: [Palacio Barolo, symbolicStoreysCount, related to the 100 cantos of the Divine Comedy]
-
A.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
C.
storeysOfTallestTower
Indicates the number of storeys contained in the tallest tower associated with the given context or entity.
-
D.
numberOfStairs
Indicates the quantity of stairs associated with or present in a given context or structure.
-
E.
floorCountApproximate
Indicates an approximate or estimated number of floors associated with a building or structure.
- F. None of above. chosen
Provenance (4 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_69f01a58a67c819097936d9e8da8d6e6 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6622808b48190bbabcc75288ab031 |
completed | May 2, 2026, 8:44 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f6617a7e7c81908cfac4a2250797ee |
completed | May 2, 2026, 8:41 p.m. |
Created at: April 28, 2026, 2:45 a.m.