Triple
T135362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finnish language |
E2735
|
entity |
| Predicate | hasColloquialVariety |
P5203
|
FINISHED |
| Object | Colloquial Finnish |
—
|
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: Colloquial Finnish | Statement: [Finnish language, hasColloquialVariety, Colloquial Finnish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColloquialVariety Context triple: [Finnish language, hasColloquialVariety, Colloquial Finnish]
-
A.
regionalDialect
Indicates that one entity uses or is associated with a dialect specific to a particular geographic region in relation to another entity.
-
B.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
-
C.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
-
D.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
E.
recognizedRegionalLanguage
Indicates that a language holds officially recognized status within a specific region or subnational jurisdiction.
- F. None of above. chosen
Provenance (4 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a3ad908190b6a8652f09ae0cbb |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25651b9048190a6277b7fec98c1ea |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256c72f6c81909b619b90d829d86e |
completed | Feb. 28, 2026, 2:45 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.