Triple
T7156432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Sea–Mediterranean–Indian Ocean shipping route |
E166822
|
entity |
| Predicate | shortensDistanceBetween |
P12934
|
FINISHED |
| Object | Europe and Asia |
—
|
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: Europe and Asia | Statement: [Red Sea–Mediterranean–Indian Ocean shipping route, shortensDistanceBetween, Europe and Asia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shortensDistanceBetween Context triple: [Red Sea–Mediterranean–Indian Ocean shipping route, shortensDistanceBetween, Europe and Asia]
-
A.
significantlyShortensRouteBetween
chosen
Indicates that one entity provides a connection between two others that makes the path or travel distance between them substantially shorter than alternative routes.
-
B.
shortensBefore
Indicates that one entity causes another entity’s duration, length, or extent to become shorter prior to a specified reference point or event.
-
C.
closerTo
Indicates that one entity is at a smaller distance to a reference entity than another entity is.
-
D.
distance
Indicates the spatial separation or length between two points, objects, or locations.
-
E.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
- 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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e80dafdc8190b24863b83f084d12 |
completed | March 27, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69c6e1caf4e48190b47bb398a3c1554d |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:47 p.m.