Triple
T15015931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohio-class ballistic missile submarine |
E377959
|
entity |
| Predicate | numberOfSSBNConfiguredBoats |
P106331
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Ohio-class ballistic missile submarine, numberOfSSBNConfiguredBoats, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSSBNConfiguredBoats Context triple: [Ohio-class ballistic missile submarine, numberOfSSBNConfiguredBoats, 14]
-
A.
numberOfSSBNConfiguredUnits
chosen
Indicates the quantity of SSBN-configured units associated with or assigned to a given entity.
-
B.
numberOfSSGNConfiguredUnits
Indicates the quantity of SSGN-configured units associated with or defined for a given entity or system.
-
C.
missileTubesPerBoat
Indicates the number of missile tubes associated with each individual boat in the relationship.
-
D.
numberOfShips
Indicates the quantity of ships associated with a given entity or situation.
-
E.
numberOfNaves
Indicates the specific count of naves (longitudinal sections) that a building, typically a church, possesses.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7623c3c819092ca36b358b01842 |
completed | April 15, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:55 a.m.