Triple
T7186084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vichada Department |
E167573
|
entity |
| Predicate | hasMainTransportMode |
P70707
|
FINISHED |
| Object | river transport |
—
|
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: river transport | Statement: [Vichada Department, hasMainTransportMode, river transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainTransportMode Context triple: [Vichada Department, hasMainTransportMode, river transport]
-
A.
hasPrimaryTransportationMode
chosen
Indicates the main or most frequently used mode of transportation associated with an entity.
-
B.
hasSecondaryTransportationMode
Indicates that an entity is associated with an additional, non-primary mode of transportation it can use or provide.
-
C.
hasTransportRoute
Indicates that there exists a designated transportation connection or route linking one entity to another.
-
D.
hasPublicTransitMode
Indicates that a location, route, or service is associated with or supports a specific mode of public transportation (e.g., bus, train, tram).
-
E.
hasTransportationRelation
Indicates a relationship in which one entity provides, uses, is connected by, or is otherwise associated with a means or mode of transportation to another entity or location.
- 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_69c6888a7c548190a3d39b52a393080f |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9b045c48190b27b2d6f7c11026f |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e74fb0f48190b2ad4dd4efdd241a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:49 p.m.