Triple
T6925242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Limburg |
E160288
|
entity |
| Predicate | hasDialectFeature |
P28371
|
FINISHED |
| Object | use of Limburgish in daily life |
—
|
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: use of Limburgish in daily life | Statement: [Central Limburg, hasDialectFeature, use of Limburgish in daily life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialectFeature Context triple: [Central Limburg, hasDialectFeature, use of Limburgish in daily life]
-
A.
haveDialect
chosen
Indicates that an entity uses, speaks, or is associated with a particular dialect or regional linguistic variety.
-
B.
hasDialectCounterpart
Indicates that one linguistic form or expression has a corresponding equivalent in another dialect.
-
C.
hasDialects
Indicates that an entity (typically a language) possesses one or more distinct dialectal varieties.
-
D.
usesDialect
Indicates that one entity communicates or expresses itself using the specific dialect associated with another entity.
-
E.
hasDialectStatus
Indicates that one language variety holds a particular dialect-related status or classification in relation to another language or linguistic 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_69c6884d350081908d8a970e4d40ad78 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da18b6388190947dfc1eb9e5d382 |
completed | March 27, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bb577c81908ee8b415b4281f3d |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:26 p.m.