Triple
T32523145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King of the Belgians on judicial appointments |
E831234
|
entity |
| Predicate | appointmentInstrument |
P1030
|
FINISHED |
| Object | royal decree of appointment |
—
|
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: royal decree of appointment | Statement: [King of the Belgians on judicial appointments, appointmentInstrument, royal decree of appointment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appointmentInstrument Context triple: [King of the Belgians on judicial appointments, appointmentInstrument, royal decree of appointment]
-
A.
appointmentType
Indicates the specific category or nature of an appointment associated with an entity or event.
-
B.
appointmentMethod
chosen
Indicates how an appointment is arranged, such as the channel, process, or means used to schedule it.
-
C.
appointmentScheduledVia
Indicates that an appointment was scheduled using a particular method, channel, or system.
-
D.
appointmentBody
Indicates that one entity serves as the main content or body text associated with a particular appointment.
-
E.
appointmentTerm
Indicates the duration or specific period for which an appointment, position, or role is held.
- 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_69f34923e1548190be0524205d8cdf8f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 1, 2026, 1:01 a.m.