Triple
T14056012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frederik’s Church |
E338220
|
entity |
| Predicate | numberOfColumnsInColonnade |
P112654
|
FINISHED |
| Object | 30 |
—
|
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: 30 | Statement: [Frederik’s Church, numberOfColumnsInColonnade, 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfColumnsInColonnade Context triple: [Frederik’s Church, numberOfColumnsInColonnade, 30]
-
A.
hasColonnade
Indicates that one entity features or is characterized by a colonnade in relation to another entity.
-
B.
numberOfColumnsOnFlanks
Indicates the count of columns located on the flanking sides of a structure or object.
-
C.
numberOfCaryatids
Indicates the quantity of caryatids associated with or present on a given entity.
-
D.
hasNumberOfStandingColumns
Indicates the relationship specifying how many standing columns an entity currently has.
-
E.
numberOfColumnsPerShortSide
Indicates the count of columns that appear along each of the shorter sides of a rectangular or similarly shaped structure or layout.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c8d1aa48190a5055d15d9fa220c |
completed | April 14, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:20 p.m.