Triple
T5210274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officer of the Order of Australia |
E117613
|
entity |
| Predicate | dateOfFirstAppointments |
P27235
|
FINISHED |
| Object | 1975 |
—
|
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: 1975 | Statement: [Officer of the Order of Australia, dateOfFirstAppointments, 1975]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dateOfFirstAppointments Context triple: [Officer of the Order of Australia, dateOfFirstAppointments, 1975]
-
A.
firstReachedDate
chosen
Indicates the date on which a particular entity first achieved, accessed, or arrived at a specified state, location, or milestone.
-
B.
admissionDate
Indicates the date on which an entity (such as a person, application, or item) is formally admitted, accepted, or entered into a system or institution.
-
C.
lastAppointments
Indicates that the referenced appointments are the most recent ones associated with a given entity or context.
-
D.
firstIntroductionDate
Indicates the date on which an entity was first introduced or presented for the first time.
-
E.
firstEntranceClearedDate
Indicates the date on which an entity’s initial entrance, access, or admission was officially cleared or approved.
- 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_69bd4464ba3c8190bc16b2ebbe42ddb0 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a703e388190845dedd17252ddde |
completed | March 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69bd77bb4e8c819094b5ac7cf61512f9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:47 p.m.