Triple
T20955644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lusophone Africa |
E516093
|
entity |
| Predicate | hasCommonColonialLanguage |
P82461
|
FINISHED |
| Object | Portuguese |
—
|
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: Portuguese | Statement: [Lusophone Africa, hasCommonColonialLanguage, Portuguese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonColonialLanguage Context triple: [Lusophone Africa, hasCommonColonialLanguage, Portuguese]
-
A.
hasSharedColonialHistory
Indicates that the related entities were subject to, or part of, the same colonial power or colonial system during a historical period.
-
B.
languageOfColonialSettlers
chosen
Indicates the language historically spoken by colonial settlers in a given place or context.
-
C.
hasColonialHistoryWith
Indicates that one entity has a historical relationship of colonization or being colonized involving the other entity.
-
D.
hasLinguisticHeritage
Indicates that one entity possesses or is associated with the linguistic background, tradition, or ancestry of another entity.
-
E.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
- 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_69e0b4fcd678819087a304291f14330a |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fb6b19048190b266ed24f6fc1a97 |
completed | April 21, 2026, 4:22 a.m. |
| PD | Predicate disambiguation | batch_69e5c9b1bae48190a845165fed1b005e |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 1:28 p.m.