Triple
T376193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabon |
E8377
|
entity |
| Predicate | colonialHistory |
P3812
|
FINISHED |
| Object | former French colony |
—
|
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: former French colony | Statement: [Gabon, colonialHistory, former French colony]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colonialHistory Context triple: [Gabon, colonialHistory, former French colony]
-
A.
colonialLegacy
Indicates the enduring influence or consequences of a past colonial relationship that continue to shape interactions or conditions between entities.
-
B.
hasColonialHistoryWith
chosen
Indicates that one entity has a historical relationship of colonization or being colonized involving the other entity.
-
C.
hadColonialAdministrationType
Indicates the specific form or system of colonial governance that was exercised over a territory or population.
-
D.
wasColonialPower
Indicates that one entity historically exercised colonial control or dominance over another entity.
-
E.
colonialOffshoot
Indicates that one entity originated as a colony or derivative settlement established by another entity.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec169a848190a577aa093c878839 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96351cc8190a55adf95f8c27e9e |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.