Triple
T27700673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS John F. Kennedy (CVN-79) |
E698418
|
entity |
| Predicate | previousNamesakeShip |
P157428
|
FINISHED |
| Object | USS John F. Kennedy (CV-67) |
—
|
NE NERFINISHED |
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: USS John F. Kennedy (CV-67) | Statement: [USS John F. Kennedy (CVN-79), previousNamesakeShip, USS John F. Kennedy (CV-67)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousNamesakeShip Context triple: [USS John F. Kennedy (CVN-79), previousNamesakeShip, USS John F. Kennedy (CV-67)]
-
A.
namesakeShip
chosen
Indicates that one entity is a ship that is named after, or serves as the namesake of, another entity.
-
B.
previousShipClass
Indicates that one ship class directly precedes another in a sequence or lineage of ship classes.
-
C.
shipName
Indicates the name assigned to a specific ship in the relationship.
-
D.
shipyardFormerName
Indicates that a shipyard previously operated under a different name, specifying what that former name was.
-
E.
notableShip
Indicates that there is a notable or significant ship associated with the subject entity.
- 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_69ef590ea74081908f0cd7500d85fa27 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: April 27, 2026, 2:56 p.m.