Triple
T5386191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turinese Piedmontese |
E120204
|
entity |
| Predicate | hasDialectalStatus |
P24201
|
FINISHED |
| Object | urban standard |
—
|
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: urban standard | Statement: [Turinese Piedmontese, hasDialectalStatus, urban standard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialectalStatus Context triple: [Turinese Piedmontese, hasDialectalStatus, urban standard]
-
A.
hasDialectStatus
chosen
Indicates that one language variety holds a particular dialect-related status or classification in relation to another language or linguistic standard.
-
B.
hasDialectContinuumWith
Indicates that two languages or dialects are part of a continuous chain of mutually intelligible varieties, without a clear boundary separating them.
-
C.
hasTraditionalDialect
Indicates that an entity possesses or is associated with a traditional form or variety of a language or dialect.
-
D.
hasDialectsIn
Indicates that a language or linguistic variety possesses distinct dialects that are used or found within a specified region or context.
-
E.
hasColloquialVariety
Indicates that one linguistic form, expression, or variety is an informal, colloquial counterpart or version of another.
- 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_69bd46354c648190a38b26f107010a96 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd86f6f39c8190aa6af12370e3d12b |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd8463a9c88190bd760378f3026180 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:03 p.m.