Triple
T10624504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shoei Kisen Kaisha |
E250286
|
entity |
| Predicate | roleInEverGivenIncident |
P95034
|
FINISHED |
| Object | registered owner of Ever Given |
—
|
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: registered owner of Ever Given | Statement: [Shoei Kisen Kaisha, roleInEverGivenIncident, registered owner of Ever Given]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInEverGivenIncident Context triple: [Shoei Kisen Kaisha, roleInEverGivenIncident, registered owner of Ever Given]
-
A.
roleInBeltAndRoad
Indicates the specific function, involvement, or capacity an entity has within the context of the Belt and Road Initiative.
-
B.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
C.
roleOfPeopleOnIt
Indicates the specific roles or functions that people have in relation to a particular object, event, or context.
-
D.
roleInEngine
Indicates the specific function or responsibility an entity has within an engine or engine-like system.
-
E.
shipInvolved
Indicates that a ship participates in, is associated with, or plays a role in a specified event or situation.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df7fe9fc81908b3b8d1dc06a829c |
completed | April 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69d6dd7fae088190973f70c69738af49 |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df463ea8819091d6683e476b4f21 |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 8:53 p.m.