Triple
T2490819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novoslobodskaya |
E52035
|
entity |
| Predicate | numberOfStainedGlassPanels |
P39764
|
FINISHED |
| Object | 32 |
—
|
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: 32 | Statement: [Novoslobodskaya, numberOfStainedGlassPanels, 32]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStainedGlassPanels Context triple: [Novoslobodskaya, numberOfStainedGlassPanels, 32]
-
A.
numberOfGlassPanes
Indicates the quantity of individual glass panes associated with or contained in an object or structure.
-
B.
numberOfGalleries
Indicates the total count of galleries associated with or contained by a given entity.
-
C.
estimatedNumberOfPaintings
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
-
D.
numberOfChandeliers
Indicates the quantity of chandeliers associated with a given entity or context.
-
E.
numberOfPavilions
Indicates the total count of pavilions associated with a given entity or context.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd18fe32081909580c6272a6013c5 |
completed | March 7, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1318f7881908a8fc42943df4879 |
completed | March 7, 2026, 7:18 a.m. |
Created at: March 6, 2026, 9:45 p.m.