Triple
T7831073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Goole |
E181367
|
entity |
| Predicate | hasCargoHandlingMode |
P79260
|
FINISHED |
| Object | multimodal 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: multimodal transport | Statement: [Port of Goole, hasCargoHandlingMode, multimodal transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCargoHandlingMode Context triple: [Port of Goole, hasCargoHandlingMode, multimodal transport]
-
A.
hasPassengerHandling
Indicates that an entity is responsible for or involved in managing the processes and services related to handling passengers.
-
B.
hasCargoServices
Indicates that an entity provides or is equipped to handle cargo transportation or freight services for another entity or location.
-
C.
hasCargoAirline
Indicates that one entity operates as a cargo airline for, or provides cargo air transport services to, another entity.
-
D.
hasCargoDivision
Indicates that an organization possesses a specific division or unit responsible for cargo-related operations or services.
-
E.
hasCargoTerminal
Indicates that a location or facility includes or is equipped with a cargo terminal for handling freight.
- F. None of above. chosen
Provenance (4 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_69ca8282ccec819083c48efb72d21cf9 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb0647848081908d74e09f52d0919e |
completed | March 30, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69cae91ae008819098e56bbe51143b31 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:44 p.m.