Triple
T10624800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ever Grade |
E250294
|
entity |
| Predicate | IMOCategory |
P95040
|
FINISHED |
| Object | cargo ship |
—
|
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: cargo ship | Statement: [Ever Grade, IMOCategory, cargo ship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: IMOCategory Context triple: [Ever Grade, IMOCategory, cargo ship]
-
A.
shipClass
Indicates the classification or type category to which a particular ship belongs.
-
B.
tonnageClass
Indicates a classification relationship where an entity is assigned to a category based on its tonnage (weight or carrying capacity range).
-
C.
hullType
Indicates the specific structural design or configuration of an object's hull, typically classifying how its outer body or shell is shaped or constructed.
-
D.
craftType
Indicates the specific kind or category of craft or vessel associated with an entity.
-
E.
shipTypeInvolved
Indicates that a particular type or class of ship is involved or participates in a specified event, situation, or relationship.
- 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.