Triple
T4132696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Ubangi-Shari |
E85076
|
entity |
| Predicate | dateBecamePartOfFrenchEquatorialAfrica |
P9430
|
FINISHED |
| Object | 1910 |
—
|
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: 1910 | Statement: [French Ubangi-Shari, dateBecamePartOfFrenchEquatorialAfrica, 1910]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dateBecamePartOfFrenchEquatorialAfrica Context triple: [French Ubangi-Shari, dateBecamePartOfFrenchEquatorialAfrica, 1910]
-
A.
annexedInYear
chosen
Indicates that one entity was formally annexed or incorporated into another in the specified calendar year.
-
B.
annexationDate
Indicates the date on which one entity formally annexed or incorporated another entity into its territory or jurisdiction.
-
C.
locatedInFormerColonyOf
Indicates that one entity is geographically situated within a territory that was formerly a colony of another entity.
-
D.
integratedIntoFrenchCrown
Indicates that a territory, institution, or authority was formally absorbed into and brought under the direct control of the French royal state.
-
E.
wasUnderTrusteeshipOf
Indicates that one entity was administered, overseen, or managed under the legal or formal trusteeship authority of 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af01883b6c8190a482ead589a131a5 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:42 p.m.