Triple
T20575877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of St. Ignatius of Loyola at Campus Martius |
E505215
|
entity |
| Predicate | hasNumberOfNaves |
P17652
|
FINISHED |
| Object | one nave |
—
|
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: one nave | Statement: [Church of St. Ignatius of Loyola at Campus Martius, hasNumberOfNaves, one nave]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfNaves Context triple: [Church of St. Ignatius of Loyola at Campus Martius, hasNumberOfNaves, one nave]
-
A.
numberOfNaves
chosen
Indicates the specific count of naves (longitudinal sections) that a building, typically a church, possesses.
-
B.
hasNave
Indicates that one entity (typically a building or structure) possesses or includes a nave as a distinct architectural part.
-
C.
hasNavePlan
Indicates that an entity possesses or is associated with a specific plan or layout for a nave (the central part of a church or similar building).
-
D.
hasNavalComponent
Indicates that something includes, involves, or is associated with a naval or maritime element as part of its composition or structure.
-
E.
numberOfShips
Indicates the quantity of ships associated with a given entity or situation.
- 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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a90af3608190955d2c7950726178 |
completed | April 20, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69e59ff0116c8190a163ff28ed01430a |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:39 a.m.