Triple
T8226545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Classis Africana |
E192186
|
entity |
| Predicate | operationalRoute |
P21808
|
FINISHED |
| Object | between North Africa and Italy |
—
|
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: between North Africa and Italy | Statement: [Classis Africana, operationalRoute, between North Africa and Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operationalRoute Context triple: [Classis Africana, operationalRoute, between North Africa and Italy]
-
A.
operatedRoutes
Indicates that an agent (such as a company or organization) runs or manages specific routes, typically providing services along those paths.
-
B.
operatedOnRoute
chosen
Indicates that a transportation service or vehicle was active and provided service along a specified route.
-
C.
routeDescription
Indicates a textual explanation or summary of the path, course, or itinerary taken between locations.
-
D.
routesFrom
Indicates that something (such as a path, connection, or communication) originates at one entity and is directed or carried from that source entity toward another.
-
E.
routeOptimization
Indicates the process of determining the most efficient path or sequence of paths between locations according to specified criteria such as distance, time, or cost.
- 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_69ca82db5b90819085d1ad7c2e27bfcc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb77fc10f48190b7e241c89885a478 |
completed | March 31, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69cb36af41e081909dee92b9bc4947f1 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:45 p.m.