Triple
T38101328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ibirama |
E951385
|
entity |
| Predicate | hasSignificantGermanSpeakingPopulation |
P61052
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ibirama, hasSignificantGermanSpeakingPopulation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignificantGermanSpeakingPopulation Context triple: [Ibirama, hasSignificantGermanSpeakingPopulation, true]
-
A.
containsGermanSpeakingArea
Indicates that one entity geographically includes an area where German is predominantly spoken.
-
B.
cityWithLargeGermanImmigrantPopulation
Indicates that a city has a notably large population of residents who are immigrants from Germany.
-
C.
ethnicallyGermanizedBy
Indicates that an entity has adopted or been assimilated into German ethnic identity, culture, or characteristics as a result of influence or actions by another entity.
-
D.
hasOfficialLanguageNameInGerman
Indicates that an entity has an official language name expressed specifically in the German language.
-
E.
demographicsSignificantLanguage
chosen
Indicates that a particular language is significantly represented or prevalent within the demographic profile of a population or group.
- 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_69f76f04960c8190a83f14ae4c67f5bc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: May 3, 2026, 4:21 p.m.