Triple
T2378564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Court of Appeal of New Zealand |
E46257
|
entity |
| Predicate | maximumPanelSize |
P38342
|
FINISHED |
| Object | 5 judges |
—
|
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: 5 judges | Statement: [Court of Appeal of New Zealand, maximumPanelSize, 5 judges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumPanelSize Context triple: [Court of Appeal of New Zealand, maximumPanelSize, 5 judges]
-
A.
maximumVolumeSize
Indicates the largest allowable size or capacity that a volume can have within a given system or context.
-
B.
typicalPanelSize
Indicates the usual or standard dimensions associated with a given panel.
-
C.
maximumCapacity
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
-
D.
maximumExtent
Indicates the greatest or furthest degree, size, or range to which something can extend or apply within a given context.
-
E.
maximumChannelWidth
Indicates the greatest allowable or observed width of a channel in the given 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7974aa481908799ef2f854d1c9d |
completed | March 7, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69abc59f73f08190924a36d7d475d8f4 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6f4245881909282b3184a288e2a |
completed | March 7, 2026, 6:34 a.m. |
Created at: March 4, 2026, 7:57 p.m.