Triple
T22345118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Askernish Golf Club |
E552370
|
entity |
| Predicate | hasRegionalLanguageEnvironment |
P145769
|
FINISHED |
| Object | Scottish Gaelic |
—
|
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: Scottish Gaelic | Statement: [Askernish Golf Club, hasRegionalLanguageEnvironment, Scottish Gaelic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalLanguageEnvironment Context triple: [Askernish Golf Club, hasRegionalLanguageEnvironment, Scottish Gaelic]
-
A.
hasLanguageRegionContext
Indicates that something is associated with or situated within a specific linguistic or language-region context.
-
B.
hasTraditionalLanguageRegion
Indicates the geographic region traditionally associated with the use or origin of a particular language.
-
C.
recognizedRegionalLanguage
Indicates that a language holds officially recognized status within a specific region or subnational jurisdiction.
-
D.
hasSuccessorLanguageInRegion
Indicates that one language is followed or replaced by another language within a specific geographic region.
-
E.
subjectLanguageRegion
chosen
Indicates that the subject is associated with or uses a language specific to a particular geographic region.
- 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_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157975db481909db65ff4d8505bbd |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:43 p.m.