Triple
T302035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sims-class destroyer |
E6217
|
entity |
| Predicate | hullNumberRange |
P11282
|
FINISHED |
| Object | DD-409 to DD-420 |
—
|
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: DD-409 to DD-420 | Statement: [Sims-class destroyer, hullNumberRange, DD-409 to DD-420]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hullNumberRange Context triple: [Sims-class destroyer, hullNumberRange, DD-409 to DD-420]
-
A.
hullNumber
Indicates the unique identifying number assigned to the hull of a ship or vessel.
-
B.
hullType
Indicates the specific structural design or configuration of an object's hull, typically classifying how its outer body or shell is shaped or constructed.
-
C.
shipClass
Indicates the classification or type category to which a particular ship belongs.
-
D.
fleetSize
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet associated with an entity.
-
E.
harborType
Indicates the specific kind or classification of a harbor associated with an entity.
- 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_69a2e79230508190b912ecb555aae17e |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93c367881908d3f6e2b81d44d7f |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea2af1388190b93235602ace679e |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.