Triple
T10286624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winkie Country |
E241243
|
entity |
| Predicate | inhabitantDemonym |
P21261
|
FINISHED |
| Object | Winkies |
—
|
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: Winkies | Statement: [Winkie Country, inhabitantDemonym, Winkies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inhabitantDemonym Context triple: [Winkie Country, inhabitantDemonym, Winkies]
-
A.
populationDemonym
chosen
Indicates the term used to refer to the people or inhabitants associated with a particular place or region.
-
B.
relatedDemonym
Indicates that one entity is the demonym (name for residents or natives) associated with the other entity.
-
C.
languageInhabitants
Indicates that a particular language is spoken or used by the inhabitants of a specified place or region.
-
D.
supporterDemonym
Indicates the relationship between an entity and the demonym used to refer to its supporters or fans.
-
E.
demographicScope
Indicates the specific population group or demographic segment to which something (e.g., a policy, study, product, or service) is targeted or applicable.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:40 a.m.