Triple
T7471120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chagatai script |
E176505
|
entity |
| Predicate | orthographyFeatures |
P18322
|
FINISHED |
| Object | adapted Arabic letters for Turkic sounds |
—
|
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: adapted Arabic letters for Turkic sounds | Statement: [Chagatai script, orthographyFeatures, adapted Arabic letters for Turkic sounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orthographyFeatures Context triple: [Chagatai script, orthographyFeatures, adapted Arabic letters for Turkic sounds]
-
A.
usesStandardOrthographyOf
Indicates that one entity writes or represents language according to the standard orthographic system defined for another entity.
-
B.
hasOrthographicConvention
Indicates that there is a specific writing or spelling convention that governs how something is represented in written form.
-
C.
orthographicVariant
Indicates that two written forms are different spellings or orthographic representations of the same linguistic item.
-
D.
hasOrthographicReform
Indicates that an entity has undergone or is associated with a change or standardization in its writing system or spelling conventions.
-
E.
writingSystemFeatures
chosen
Indicates the specific structural or functional characteristics that define how a particular writing system represents language.
- 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_69c69f223fd88190b4c69b95d7cbeeda |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f4145d608190bd93239f04f7da41 |
completed | March 27, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69c6f03d967081908a8e696ff9693b90 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:41 p.m.