Triple
T36493484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexington-class aircraft carrier |
E899113
|
entity |
| Predicate | fateOfUSS_Lexington_CV2 |
P119412
|
FINISHED |
| Object | sunk in Battle of the Coral Sea |
—
|
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: sunk in Battle of the Coral Sea | Statement: [Lexington-class aircraft carrier, fateOfUSS_Lexington_CV2, sunk in Battle of the Coral Sea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fateOfUSS_Lexington_CV2 Context triple: [Lexington-class aircraft carrier, fateOfUSS_Lexington_CV2, sunk in Battle of the Coral Sea]
-
A.
aircraftCarrierInvolved
Indicates that an aircraft carrier participates in, is present at, or is otherwise directly involved in the specified event or situation.
-
B.
aircraftCarrierOperatedFrom
Indicates that an aircraft carrier conducts its operations from, or is based at, a particular location or facility.
-
C.
fleetScuttledAt
Indicates that a fleet was deliberately sunk or destroyed at a specific location or during a specific event.
-
D.
notableVictimShip
chosen
Indicates that a ship is recognized as a particularly significant or noteworthy victim in a specific incident or context.
-
E.
hullLoss
Indicates that an aircraft has suffered damage or destruction severe enough to be considered a total loss of the airframe.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.