Triple
T4522618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Church (Delft) |
E103302
|
entity |
| Predicate | hasWindow |
P8656
|
FINISHED |
| Object | commemorative stained glass windows |
—
|
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: commemorative stained glass windows | Statement: [Old Church (Delft), hasWindow, commemorative stained glass windows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWindow Context triple: [Old Church (Delft), hasWindow, commemorative stained glass windows]
-
A.
windowType
chosen
Indicates the specific kind or category of window associated with an entity.
-
B.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
-
C.
hasScreen
Indicates that an entity is equipped with or includes a screen or display component.
-
D.
numberOfWindows
Indicates the count of windows associated with a given entity.
-
E.
hasTab
Indicates that one entity includes, contains, or is associated with a tab element or tabbed section related to 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd574bd6908190b939d92b5809b101 |
completed | March 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69bd521cf77c819083852de3094d1377 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:02 p.m.