Triple
T5829584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bzyb dialect |
E129310
|
entity |
| Predicate | hasStatusWithinLanguage |
P25828
|
FINISHED |
| Object | non-standard regional variety |
—
|
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: non-standard regional variety | Statement: [Bzyb dialect, hasStatusWithinLanguage, non-standard regional variety]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStatusWithinLanguage Context triple: [Bzyb dialect, hasStatusWithinLanguage, non-standard regional variety]
-
A.
hasLanguageStatus
chosen
Indicates that an entity has a particular status or condition regarding its language use, recognition, or classification.
-
B.
hasStatusIn
Indicates that an entity holds or is assigned a particular status within a specified context, scope, or system.
-
C.
officialLanguageStatusSharedWith
Indicates that two entities share at least one official language in common.
-
D.
hasNotableLanguageWithOfficialStatusIn
Indicates that a language holds an officially recognized and notable status within a specified jurisdiction or region.
-
E.
languageStatusSource
Indicates the source or authority from which the information about a language’s status is derived.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.