Triple
T22082494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sawndip |
E545685
|
entity |
| Predicate | scriptReformImpact |
P5211
|
FINISHED |
| Object | partly replaced by Latin-based Zhuang script |
—
|
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: partly replaced by Latin-based Zhuang script | Statement: [Sawndip, scriptReformImpact, partly replaced by Latin-based Zhuang script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptReformImpact Context triple: [Sawndip, scriptReformImpact, partly replaced by Latin-based Zhuang script]
-
A.
scriptAfterReform
chosen
Indicates that one script or writing system is used after a reform or modification has been applied to another script.
-
B.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
-
C.
scriptInfluence
Indicates that one script affects, shapes, or alters the behavior, outcome, or characteristics of another entity (such as another script, process, or system).
-
D.
chartImpact
Indicates how one factor or action influences the shape, position, or behavior of a chart or graphical representation.
-
E.
regulationImpact
Indicates how a regulation influences, constrains, or alters the behavior, performance, or outcomes associated with the related entities.
- 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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b706288190945c0c37e5ff2756 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e71b20ec50819096ac196c798f8e3c |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:28 p.m.