Triple
T32538738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | modern France |
E831658
|
entity |
| Predicate | formerColonialEmpire |
P59055
|
FINISHED |
| Object | French colonial empire |
—
|
NE NERFINISHED |
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: French colonial empire | Statement: [modern France, formerColonialEmpire, French colonial empire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerColonialEmpire Context triple: [modern France, formerColonialEmpire, French colonial empire]
-
A.
wasColonialPower
Indicates that one entity historically exercised colonial control or dominance over another entity.
-
B.
imperialPossessions
Indicates that one entity holds colonial or territorial control over another as part of its empire.
-
C.
formerColonialStatus
chosen
Indicates that one entity previously held colonial authority or control over another entity, but that colonial relationship has since ended.
-
D.
partOfColonialEntity
Indicates that one entity is a constituent or subordinate territorial unit within a larger colonial political or administrative entity.
-
E.
formerColonialPowerTargeted
Indicates that the subject was previously a colonial power that is now being targeted or opposed by the object.
- 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_69f34924b1cc8190ad3aca0c0f012a7e |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff878f41888190bcb3bc41ad26081a |
completed | May 9, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69ff854082d88190aad3bfedf05e849f |
completed | May 9, 2026, 7:04 p.m. |
Created at: May 1, 2026, 1:02 a.m.