Triple
T32319833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue triptych |
E825743
|
entity |
| Predicate | hasPanelCountConstraint |
P40883
|
FINISHED |
| Object | exactly three pieces |
—
|
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: exactly three pieces | Statement: [Blue triptych, hasPanelCountConstraint, exactly three pieces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPanelCountConstraint Context triple: [Blue triptych, hasPanelCountConstraint, exactly three pieces]
-
A.
hasComponentCount
Indicates that an entity is associated with a specific number of components it contains or comprises.
-
B.
hasPanelComposition
Indicates that something is composed of or structured into multiple panels or panel-like sections.
-
C.
hasPanelFormat
Indicates that something is associated with a particular panel layout or format used for its presentation or display.
-
D.
hasNumberOfPaintedPanels
Indicates the relationship specifying how many panels in an object or structure are painted.
-
E.
numberOfPanels
chosen
Indicates the total count of distinct panels associated with or contained within a given 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_69f34912d0c48190bba75770660320e9 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fefb15220081908da36aac386fa582 |
completed | May 9, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_69fefa8e8ad48190a723fed81e9d64d0 |
completed | May 9, 2026, 9:12 a.m. |
Created at: May 1, 2026, 12:46 a.m.