Triple
T12718659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohio-class submarine |
E303915
|
entity |
| Predicate | numberOfSSGNConfiguredUnits |
P106332
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Ohio-class submarine, numberOfSSGNConfiguredUnits, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSSGNConfiguredUnits Context triple: [Ohio-class submarine, numberOfSSGNConfiguredUnits, 4]
-
A.
numberOfShips
Indicates the quantity of ships associated with a given entity or situation.
-
B.
fleetSize
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet associated with an entity.
-
C.
numberOfMissileTubes
Indicates the quantity of missile tubes that an entity possesses or is equipped with.
-
D.
missileTubesPerBoat
Indicates the number of missile tubes associated with each individual boat in the relationship.
-
E.
navalForceComposition
Indicates the makeup and distribution of different types of naval units or vessels within a particular naval force.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9625d9da48190ab377f9328a0e1f5 |
completed | April 10, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69d960c088dc8190b0e63312c54e4c6c |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d961acadb8819098de743bc951fedb |
completed | April 10, 2026, 8:46 p.m. |
Created at: April 9, 2026, 5:23 p.m.