Triple
T15231689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justice of the Supreme Court of the United Kingdom |
E364017
|
entity |
| Predicate | possiblePanelSize |
P38342
|
FINISHED |
| Object | 3 justices |
—
|
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: 3 justices | Statement: [Justice of the Supreme Court of the United Kingdom, possiblePanelSize, 3 justices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: possiblePanelSize Context triple: [Justice of the Supreme Court of the United Kingdom, possiblePanelSize, 3 justices]
-
A.
maximumPanelSize
chosen
Indicates the largest allowable or supported size for a given panel in the specified context.
-
B.
typicalPanelSize
Indicates the usual or standard dimensions associated with a given panel.
-
C.
numberOfPanels
Indicates the total count of distinct panels associated with or contained within a given entity.
-
D.
paletteSize
Indicates the number of distinct colors included in a given color palette.
-
E.
hasPanel
Indicates that one entity includes, is equipped with, or is associated with a panel as a component or feature.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078e27408190bc13c0ca441f5594 |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca899d5c8190be4a7c71e1683c69 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:12 a.m.