Triple
T16169488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kedukan Bukit |
E392395
|
entity |
| Predicate | inscriptionNumberOfLines |
P121966
|
FINISHED |
| Object | several lines of text |
—
|
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: several lines of text | Statement: [Kedukan Bukit, inscriptionNumberOfLines, several lines of text]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inscriptionNumberOfLines Context triple: [Kedukan Bukit, inscriptionNumberOfLines, several lines of text]
-
A.
inscriptionNumber
Indicates the identifying number assigned to a specific inscription within a collection or system.
-
B.
inscriptionIncludesLine
Indicates that an inscription contains a specific line of text as one of its components.
-
C.
numberOfInscriptions
Indicates the total count of inscriptions associated with a given entity or object.
-
D.
signCount
Indicates the number of signs associated with, produced by, or present in relation to a given entity or context.
-
E.
inscriptionID
Indicates a unique identifier that links an entity to a specific inscription or inscribed text.
- 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_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. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:02 a.m.