Triple
T362458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supreme Court of New Zealand |
E7885
|
entity |
| Predicate | maximumNumberOfJudges |
P2279
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Supreme Court of New Zealand, maximumNumberOfJudges, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumNumberOfJudges Context triple: [Supreme Court of New Zealand, maximumNumberOfJudges, 6]
-
A.
numberOfJudges
chosen
Indicates the total count of judges associated with a particular case, event, or entity.
-
B.
judgesTerm
Indicates that one entity formally evaluates or makes a judgment about a specific term or expression.
-
C.
numberOfCourts
Indicates the quantity of courts associated with or present at a given entity or location.
-
D.
maximumNumberOfKnightsAndLadies
Indicates the greatest allowable or observed count of entities classified as knights and ladies within a given context or scenario.
-
E.
judge
Indicates that one entity evaluates, forms an opinion about, or makes a decision regarding another entity or situation.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebcfb0f48190b9a9010c7837ac58 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95c843c8190b2aba9af6e869ba1 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.