Triple
T20142916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wetu Telu Islam |
E491219
|
entity |
| Predicate | hasClericalFigure |
P9815
|
FINISHED |
| Object | kyai |
—
|
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: kyai | Statement: [Wetu Telu Islam, hasClericalFigure, kyai]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClericalFigure Context triple: [Wetu Telu Islam, hasClericalFigure, kyai]
-
A.
hasClericalProtagonist
Indicates that the main character in the work is a member of the clergy or holds a religious office.
-
B.
hasClericalFunction
Indicates that an entity performs, is responsible for, or is associated with a clerical or administrative function.
-
C.
hasClericalArtist
Indicates that an entity is associated with a clerical artist who performed or contributed clerical or calligraphic work for it.
-
D.
isClericIn
Indicates that an entity serves or functions as a cleric within a specified organization, location, or group.
-
E.
hasClergy
chosen
Indicates that an organization or institution possesses or is served by members of the clergy.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679bcf2c8190ac6e969178d8acde |
completed | April 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:33 p.m.