Triple
T16169472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kedukan Bukit |
E392395
|
entity |
| Predicate | inscriptionContentTheme |
P33353
|
FINISHED |
| Object | royal expedition |
—
|
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 expedition | Statement: [Kedukan Bukit, inscriptionContentTheme, royal expedition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inscriptionContentTheme Context triple: [Kedukan Bukit, inscriptionContentTheme, royal expedition]
-
A.
signatureTheme
Indicates that something serves as a distinctive, defining theme strongly associated with a particular entity or context.
-
B.
inscriptionContentType
chosen
Indicates the type or nature of the content conveyed by an inscription (e.g., its genre, function, or informational category).
-
C.
inscriptionFeature
Indicates that one entity bears or contains an inscribed element or marking that is treated as a notable feature in relation to another entity.
-
D.
inscriptionLayout
Indicates how an inscription is spatially arranged or formatted in relation to the surface or object it appears on.
-
E.
inscriptionType
Indicates the specific kind or category of inscription associated with an entity (e.g., dedicatory, funerary, commemorative).
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb5e6d881908749683091afa90c |
completed | April 17, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.