Triple
T8570339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Facade of Santa Maria Novella, Florence |
E202909
|
entity |
| Predicate | hasLowerPartFrom |
P35
|
FINISHED |
| Object | 14th century |
—
|
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: 14th century | Statement: [Facade of Santa Maria Novella, Florence, hasLowerPartFrom, 14th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLowerPartFrom Context triple: [Facade of Santa Maria Novella, Florence, hasLowerPartFrom, 14th century]
-
A.
hasLowerDeckFunction
Indicates that an entity serves a specific role or performs a designated function on the lower deck of a structure or vehicle.
-
B.
hasPart
chosen
Indicates that one entity is a component, segment, or constituent part of another entity.
-
C.
hasLower
Indicates that one entity is positioned at a lower level, rank, or value relative to another entity.
-
D.
hasLowerTier
Indicates that one entity is ranked, valued, or classified at a lower level or tier relative to another entity.
-
E.
hasLowerBarLength
Indicates that one entity’s bar length is shorter than the bar length of another entity.
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea4091f48190b5174d7a5cfd2bd8 |
completed | March 31, 2026, 3:37 p.m. |
| PD | Predicate disambiguation | batch_69cbd11856048190a1ce4b83a38f6965 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:21 p.m.