Triple
T1432340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Ready Reserve Force |
E30475
|
entity |
| Predicate | hasShipType |
P11978
|
FINISHED |
| Object | roll-on/roll-off 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: roll-on/roll-off ship | Statement: [United States Ready Reserve Force, hasShipType, roll-on/roll-off ship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShipType Context triple: [United States Ready Reserve Force, hasShipType, roll-on/roll-off ship]
-
A.
hasVesselType
chosen
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
B.
hasShip
Indicates that one entity possesses, owns, or is equipped with a ship.
-
C.
shipsWith
Indicates that one entity is delivered, packaged, or provided together with another entity as part of the same shipment or bundle.
-
D.
originalShipType
Indicates the type or category of ship that an entity was originally classified or built as.
-
E.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c500a9888190a16fbb1ec97a79c9 |
completed | March 1, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69a4c4771c9481908ae47c959debbe77 |
completed | March 1, 2026, 10:57 p.m. |
Created at: March 1, 2026, 8 p.m.