Triple
T27232800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyrl |
E682198
|
entity |
| Predicate | BCP47ScriptSubtag |
P16462
|
FINISHED |
| Object | Cyrl |
—
|
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: Cyrl | Statement: [Cyrl, BCP47ScriptSubtag, Cyrl]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BCP47ScriptSubtag Context triple: [Cyrl, BCP47ScriptSubtag, Cyrl]
-
A.
associatedLanguageScript
chosen
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
B.
nativeNameScript
Indicates the writing system or script in which an entity’s native name is expressed.
-
C.
ISO639Scope
Indicates the classification of a language according to its scope, such as whether it represents an individual language, a macrolanguage, or a collection of languages.
-
D.
ISO639Macrolanguage
Indicates that a language variety is part of a broader ISO 639-defined macrolanguage grouping that encompasses multiple closely related individual languages.
-
E.
ISO639Language
Indicates that an entity is associated with a language identified or classified according to the ISO 639 language code standard.
- 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_69eefacdad7881908b7bca61c90a1a1e |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6264fe9488190b07fb4024eba323d |
completed | May 2, 2026, 4:29 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 9:46 a.m.