Triple
T37337493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wea people |
E926934
|
entity |
| Predicate | usedLanguageVariety |
P41081
|
FINISHED |
| Object | Miami-Illinois dialect |
—
|
NE NERFINISHED |
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: Miami-Illinois dialect | Statement: [Wea people, usedLanguageVariety, Miami-Illinois dialect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedLanguageVariety Context triple: [Wea people, usedLanguageVariety, Miami-Illinois dialect]
-
A.
hasLinguisticVariety
Indicates that one entity possesses or exhibits a particular linguistic variety in relation to another entity or context.
-
B.
primaryLanguageVariety
chosen
Indicates the main dialect or specific variety of a language that an entity primarily uses.
-
C.
linguisticVariation
Indicates a relationship where one linguistic form differs from another in expression, usage, or structure while remaining related in meaning or function.
-
D.
denotesLanguageVariety
Indicates that one entity specifies the particular variety, dialect, or form of language used or associated with another entity.
-
E.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
- 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_69f76eb4e8a881908bd40da28f36fc7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb8c38a9688190be524246f5682107 |
completed | May 6, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9c6e0481908565bd849e869b24 |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:16 p.m.