Triple
T7471114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chagatai script |
E176505
|
entity |
| Predicate | usedForLanguageRegister |
P19921
|
FINISHED |
| Object | high literary register |
—
|
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: high literary register | Statement: [Chagatai script, usedForLanguageRegister, high literary register]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForLanguageRegister Context triple: [Chagatai script, usedForLanguageRegister, high literary register]
-
A.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
B.
linguisticRegister
chosen
Indicates the level of formality or stylistic variety in which a linguistic expression is typically used within a given context.
-
C.
associatedLanguageRegulator
Indicates that one entity serves as the official or recognized regulatory body responsible for overseeing, standardizing, or managing the language associated with another entity.
-
D.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
E.
scriptUsedForLanguage
Indicates that a particular writing script is employed to write or represent a given 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.