Triple
T8711685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of New Zealand |
E206790
|
entity |
| Predicate | firstAppointmentsNumber |
P84018
|
FINISHED |
| Object | 12 ordinary members |
—
|
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: 12 ordinary members | Statement: [Order of New Zealand, firstAppointmentsNumber, 12 ordinary members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppointmentsNumber Context triple: [Order of New Zealand, firstAppointmentsNumber, 12 ordinary members]
-
A.
noNewAppointmentsSince
Indicates that no additional appointments have been scheduled after a specified point in time.
-
B.
lastAppointments
Indicates that the referenced appointments are the most recent ones associated with a given entity or context.
-
C.
openByAppointment
Indicates that access or availability is provided only at scheduled times arranged in advance, rather than during regular open hours.
-
D.
doctorNumber
Indicates the unique identifying number assigned to a doctor in the context of a relationship or record.
-
E.
appointmentsInvolve
Indicates that scheduled appointments include or engage specific participants, resources, or activities in the appointment event.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5c3189f88190bb9bb77ba9d28d60 |
completed | March 31, 2026, 11:43 p.m. |
| PD | Predicate disambiguation | batch_69cc456e806c819087e7d66ee737f242 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc46c40c54819093d174a4203f9515 |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:35 p.m.