Triple
T38101327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ibirama |
E951385
|
entity |
| Predicate | hasGermanColonization |
P3812
|
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, hasGermanColonization, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGermanColonization Context triple: [Ibirama, hasGermanColonization, true]
-
A.
wasColonizedIn
Indicates that a place or territory came under the control of a colonizing power in a specified time or period.
-
B.
hasColonialHistoryWith
chosen
Indicates that one entity has a historical relationship of colonization or being colonized involving the other entity.
-
C.
hasColonialHistory
Indicates that an entity has experienced or participated in a period of colonial rule, control, or administration in relation to another entity.
-
D.
countryDuringGermanRule
Indicates that one entity functioned as a country or territorial unit during a period when it was under German rule or control.
-
E.
hasGermanOccupationFunction
Indicates that an entity holds or is assigned a specific occupational role or function within the context of German administrative or professional structures.
- 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_69fe779248c081909f0ed1a2a0df23db |
completed | May 8, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69fe76eaf6d48190998bc7168749cc42 |
completed | May 8, 2026, 11:51 p.m. |
Created at: May 3, 2026, 4:21 p.m.