Triple
T8711684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of New Zealand |
E206790
|
entity |
| Predicate | firstAppointmentsYear |
P84017
|
FINISHED |
| Object | 1988 |
—
|
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: 1988 | Statement: [Order of New Zealand, firstAppointmentsYear, 1988]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppointmentsYear Context triple: [Order of New Zealand, firstAppointmentsYear, 1988]
-
A.
firstMeetingYear
Indicates the calendar year in which two entities first met or had their initial encounter.
-
B.
scheduledInYear
Indicates that an event, activity, or item is planned or set to occur within a specific calendar year.
-
C.
lastAppointments
Indicates that the referenced appointments are the most recent ones associated with a given entity or context.
-
D.
firstScreeningYear
Indicates the year in which an entity (such as a film or show) was first publicly screened or premiered.
-
E.
firstYear
Indicates that an entity is in its first year of existence, operation, or participation within a specified 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_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_69cc46c330bc8190a9b644078881c6ff |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:35 p.m.