Triple
T4837900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wrekin |
E108105
|
entity |
| Predicate | hasAssociatedDialect |
P23892
|
FINISHED |
| Object | Shropshire dialect |
—
|
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: Shropshire dialect | Statement: [The Wrekin, hasAssociatedDialect, Shropshire dialect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedDialect Context triple: [The Wrekin, hasAssociatedDialect, Shropshire dialect]
-
A.
haveDialect
Indicates that an entity uses, speaks, or is associated with a particular dialect or regional linguistic variety.
-
B.
hasDialectsIn
Indicates that a language or linguistic variety possesses distinct dialects that are used or found within a specified region or context.
-
C.
hasDialects
Indicates that an entity (typically a language) possesses one or more distinct dialectal varieties.
-
D.
hasDialectCounterpart
Indicates that one linguistic form or expression has a corresponding equivalent in another dialect.
-
E.
usesDialect
chosen
Indicates that one entity communicates or expresses itself using the specific dialect associated with another entity.
- 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c21c7f08190846049d31fdfa144 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:25 p.m.