Triple
T1877555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sundanese script |
E39177
|
entity |
| Predicate | hasEducationUse |
P23523
|
FINISHED |
| Object | taught in some schools in West Java |
—
|
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: taught in some schools in West Java | Statement: [Sundanese script, hasEducationUse, taught in some schools in West Java]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationUse Context triple: [Sundanese script, hasEducationUse, taught in some schools in West Java]
-
A.
hasEducationalUse
Indicates that something is intended to be used for educational or instructional purposes.
-
B.
usedInEducationIn
chosen
Indicates that something is employed or applied within educational contexts in a particular place or institution.
-
C.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
D.
requiresEducation
Indicates that performing or holding the related role, activity, or position depends on having a specified level or type of education.
-
E.
educationStatus
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
- 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_69a8862f7074819096afe7fe65e179e9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0f79fbc819085c54f3189a552d9 |
completed | March 7, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69abafe2b56c81909e13d543982e6e13 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.