Triple
T32934025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seri Setia Mahkota |
E842477
|
entity |
| Predicate | usesPostNominalOrder |
P129195
|
FINISHED |
| Object | after name of recipient |
—
|
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: after name of recipient | Statement: [Seri Setia Mahkota, usesPostNominalOrder, after name of recipient]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPostNominalOrder Context triple: [Seri Setia Mahkota, usesPostNominalOrder, after name of recipient]
-
A.
usesPostNominalsIn
Indicates that an entity customarily appends specific post-nominal letters to its name within a given context or jurisdiction.
-
B.
hasPostNominal
Indicates that an entity is associated with a post-nominal title, abbreviation, or letters that follow a name to denote qualifications, honors, or status.
-
C.
orderOf
Indicates that one entity is arranged, ranked, or sequenced before or after another according to a specified ordering criterion.
-
D.
usedAfterName
chosen
Indicates that one element is used or appears immediately after a name in some context or representation.
-
E.
confersOrder
Indicates that one entity formally bestows or grants an order, rank, or honorific distinction upon another entity.
- 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_69f34948adfc8190a937f1f622783c0b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 1, 2026, 1:20 a.m.