Triple
T21152106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of Santa Cristina, Turin (façade) |
E521216
|
entity |
| Predicate | hasVerticalDivision |
P98786
|
FINISHED |
| Object | two main orders |
—
|
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 main orders | Statement: [Church of Santa Cristina, Turin (façade), hasVerticalDivision, two main orders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVerticalDivision Context triple: [Church of Santa Cristina, Turin (façade), hasVerticalDivision, two main orders]
-
A.
hasNumberOfDivisions
Indicates the relationship that specifies how many divisions or subunits an entity possesses.
-
B.
hasVerticalSection
chosen
Indicates that one entity possesses or includes a distinct vertical section or segment as part of its structure or representation.
-
C.
hasDivisionRule
Indicates that one entity is governed, organized, or separated according to a specified rule or method of division defined by another entity.
-
D.
containsDivision
Indicates that one entity includes or encompasses a subdivision or internal division of another entity.
-
E.
hasDivisionLevel
Indicates that one entity is associated with a specific hierarchical or organizational division level 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_69e0b50c6a848190a4e525a77a319b8a |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7240275b481908748c0e3f187ed34 |
completed | April 21, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69e5f5f8a5bc819081918c7fa8e4496d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 2:58 p.m.